Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review
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paper_title: Long-term, year-round monitoring of wildlife crossing structures and the importance of temporal and spatial variability in performance studies

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Maintaining landscape connectivity where habitat linkages or animal migrations intersect roads requires some form of mitigation to increase permeability. Wildlife crossing structures are now being designed and incorporated into numerous road construction projects to mitigate the effects of habitat fragmentation. For them to be functional they must promote immigration and population viability. There has been a limited amount of research and information on what constitutes effective structural designs. One reason for the lack of information is because few mitigation programs implemented monitoring programs with sufficient experimental design into pre- and post-construction. Thus, results obtained from most studies remain observational at best. Furthermore, studies that did collect data in more robust manners generally failed to address the need for wildlife habituation to such large-scale landscape change. Such habituation periods can take several years depending on the species as they experience, learn and adjust their own behaviours to the wildlife structures. Also, the brief monitoring periods frequently incorporated are simply insufficient to draw on reliable conclusions. Earlier studies focused primarily on single-species crossing structure relationships, paying limited attention to ecosystem-level phenomena. The results of single species monitoring programs may fail to recognize the barrier effects imposed on other non-target species. Thus, systems can be severely compromised if land managers and transportation planners rely on simple extrapolation species. In a previous analysis of wildlife underpasses in Banff National Park (BNP), Canada, we found human influence consistently ranked high as a significant factor affecting species passage. Our results suggest that the physical dimensions of the underpasses had little effect on passage because animals may have adapted to the 12-year old underpasses. As a sequel to the above study, we examined a completely new set of recently constructed underpasses and overpasses which animals had little time to become familiar with. We investigated the importance of temporal and spatial variability using data obtained from systematic, year-round monitoring of 13 newly-constructed wildlife crossing structures 34 months post-construction. Our results suggest that structural attributes best correlated to performance indices for both large predator and prey species, while landscape and human-related factors were of secondary importance. These findings underscore the importance of integrating temporal and spatial variability as a priori when addressing wildlife crossing structure efficacy, and the fact that species respond differently to crossing structure features. Thus mitigation planning in a multiple-species ecosystem is likely to be a challenging process. The results from this work suggest that mitigation strategies need to be proactive at the site and landscape level to ensure that crossing structures remain functional over time, including human use management. Continuous long-term monitoring of crossing structures will be key to ascertaining the strengths and weaknesses of design characteristics for a multi-species assemblage
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paper_title: Spatio-temporal Relationships Among Adult Raccoons (Procyon lotor) in Central Mississippi

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Abstract We monitored 131 (99 male, 32 female) radiocollared raccoons (Procyon lotor) from January 1991 to December 1997 on the Tallahala Wildlife Management Area, Mississippi. We examined inter- and intrasexual spatial relationships and temporal interactions among adults. Adult males frequently maintained overlapping home ranges and core use areas and some males maintained spatial groups that overlapped minimally with adjacent groups or solitary males, suggesting territoriality among groups. Males arranged in spatial groups were often significantly positively associated with each other; however, we observed instances of males who remained solitary and maintained exclusive home ranges and core areas. Adult females maintained exclusive home ranges and core areas during winter, but several females shared home ranges during other seasons. However, these females did not forage or den together and were significantly negatively associated with each other within shared areas, indicating that movements by these i...
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paper_title: An emerging movement ecology paradigm

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Movement of individual organisms, one of the most fundamental features of life on Earth, is a crucial component of almost any ecological and evolutionary process, including major problems associated with habitat fragmentation, climate change, biological invasions, and the spread of pests and diseases. The rich variety of movement modes seen among microorganisms, plants, and animals has fascinated mankind since time immemorial. The prophet Jeremiah (7th century B.C.), for instance, described the temporal consistency in migratory patterns of birds, and Aristotle (4th century B.C.) searched for common features unifying animal movements (see ref. 1).
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paper_title: The interpretation of habitat preference metrics under use–availability designs

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Models of habitat preference are widely used to quantify animal-habitat relationships, to describe and predict differential space use by animals, and to identify habitat that is important to an animal (i.e. that is assumed to influence fitness). Quantifying habitat preference involves the statistical comparison of samples of habitat use and availability. Preference is therefore contingent upon both of these samples. The inferences that can be made from use versus availability designs are influenced by subjectivity in defining what is available to the animal, the problem of quantifying the accessibility of available resources and the framework in which preference is modelled. Here, we describe these issues, document the conditional nature of preference and establish the limits of inferences that can be drawn from these analyses. We argue that preference is not interpretable as reflecting the intrinsic behavioural motivations of the animal, that estimates of preference are not directly comparable among different samples of availability and that preference is not necessarily correlated with the value of habitat to the animal. We also suggest that preference is context-dependent and that functional responses in preference resulting from changing availability are expected. We conclude by describing advances in analytical methods that begin to resolve these issues.
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paper_title: Foraging theory upscaled: the behavioural ecology of herbivore movement

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We outline how principles of optimal foraging developed for diet and food patch selection might be applied to movement behaviour expressed over larger spatial and temporal scales. Our focus is on large mammalian herbivores, capable of carrying global positioning system (GPS) collars operating through the seasonal cycle and dependent on vegetation resources that are fixed in space but seasonally variable in availability and nutritional value. The concept of intermittent movement leads to the recognition of distinct movement modes over a hierarchy of spatio-temporal scales. Over larger scales, periods with relatively low displacement may indicate settlement within foraging areas, habitat units or seasonal ranges. Directed movements connect these patches or places used for other activities. Selection is expressed by switches in movement mode and the intensity of utilization by the settlement period relative to the area covered. The type of benefit obtained during settlement periods may be inferred from movement patterns, local environmental features, or the diel activity schedule. Rates of movement indicate changing costs in time and energy over the seasonal cycle, between years and among regions. GPS telemetry potentially enables large-scale movement responses to changing environmental conditions to be linked to population performance.
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paper_title: Behavioral adjustments of African herbivores to predation risk by lions: spatiotemporal variations influence habitat use.

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Predators may influence their prey populations not only through direct lethal effects, but also through indirect behavioral changes. Here, we combined spatiotemporal fine-scale data from GPS radio collars on lions with habitat use information on 11 African herbivores in Hwange National Park (Zimbabwe) to test whether the risk of predation by lions influenced the distribution of herbivores in the landscape. Effects of long-term risk of predation (likelihood of lion presence calculated over four months) and short-term risk of predation (actual presence of lions in the vicinity in the preceding 24 hours) were contrasted. The long-term risk of predation by lions appeared to influence the distributions of all browsers across the landscape, but not of grazers. This result strongly suggests that browsers and grazers, which face different ecological constraints, are influenced at different spatial and temporal scales in the variation of the risk of predation by lions. The results also show that all herbivores tend to use more open habitats preferentially when lions are in their vicinity, probably an effective anti-predator behavior against such an ambush predator. Behaviorally induced effects of lions may therefore contribute significantly to structuring African herbivore communities, and hence possibly their effects on savanna ecosystems.
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paper_title: Stochastic modelling of animal movement

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Modern animal movement modelling derives from two traditions. Lagrangian models, based on random walk behaviour, are useful for multi-step trajectories of single animals. Continuous Eulerian models describe expected behaviour, averaged over stochastic realizations, and are usefully applied to ensembles of individuals. We illustrate three modern research arenas. (i) Models of home-range formation describe the process of an animal ‘settling down’, accomplished by including one or more focal points that attract the animal's movements. (ii) Memory-based models are used to predict how accumulated experience translates into biased movement choices, employing reinforced random walk behaviour, with previous visitation increasing or decreasing the probability of repetition. (iii) Levy movement involves a step-length distribution that is over-dispersed, relative to standard probability distributions, and adaptive in exploring new environments or searching for rare targets. Each of these modelling arenas implies more detail in the movement pattern than general models of movement can accommodate, but realistic empiric evaluation of their predictions requires dense locational data, both in time and space, only available with modern GPS telemetry.
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paper_title: A line in the sand: A wireless sensor network for target detection, classification, and tracking

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Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a dense, distributed, wireless network of multi-modal resource-poor sensors combined into loosely coherent sensor arrays that perform in situ detection, estimation, compression, and exfiltration. We ground our study in the context of a security scenario called "A Line in the Sand" and accordingly define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking, and middleware services. We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of our work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effects of network unreliability on application performance. Our work includes multiple experimental deployments of over 90 sensor nodes at MacDill Air Force Base in Tampa, FL, as well as other field experiments of comparable scale. Based on these experiences, we identify a set of key lessons and articulate a few of the challenges facing extreme scaling to tens or hundreds of thousands of sensor nodes.
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paper_title: Target classification by echo locating animals

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In this paper, the principal mechanisms by which bats are assumed to classify targets are reviewed. Particular attention is paid to the ways in which bats might extract information from echoes. Classification mechanisms differ fundamentally according to signal design. It is shown how bats design their emitted waveforms according to whether they need to classify on the basis of micro-Doppler or range profile information. Throughout, analogies are made with radar (and sonar) systems, drawing attention to some ways in which engineers might learn from the classification mechanisms proposed for echo locating animals.
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paper_title: The bird GPS - long-range navigation in migrants

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SUMMARY Nowadays few people consider finding their way in unfamiliar areas a ::: problem as a GPS (Global Positioning System) combined with some simple map ::: software can easily tell you how to get from A to B. Although this opportunity ::: has only become available during the last decade, recent experiments show that ::: long-distance migrating animals had already solved this problem. Even after ::: displacement over thousands of kilometres to previously unknown areas, ::: experienced but not first time migrant birds quickly adjust their course ::: toward their destination, proving the existence of an experience-based GPS in ::: these birds. Determining latitude is a relatively simple task, even for ::: humans, whereas longitude poses much larger problems. Birds and other animals ::: however have found a way to achieve this, although we do not yet know how. ::: Possible ways of determining longitude includes using celestial cues in ::: combination with an internal clock, geomagnetic cues such as magnetic ::: intensity or perhaps even olfactory cues. Presently, there is not enough ::: evidence to rule out any of these, and years of studying birds in a laboratory ::: setting have yielded partly contradictory results. We suggest that a concerted ::: effort, where the study of animals in a natural setting goes hand-in-hand with ::: lab-based study, may be necessary to fully understand the mechanism underlying ::: the long-distance navigation system of birds. As such, researchers must remain ::: receptive to alternative interpretations and bear in mind that animal ::: navigation may not necessarily be similar to the human system, and that we ::: know from many years of investigation of long-distance navigation in birds ::: that at least some birds do have a GPS – but we are uncertain how it ::: works.
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paper_title: Self-contained Position Tracking of Human Movement Using Small Inertial/Magnetic Sensor Modules

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Numerous applications require a self-contained personal navigation system that works in indoor and outdoor environments, does not require any infrastructure support, and is not susceptible to jamming. Posture tracking with an array of inertial/magnetic sensors attached to individual human limb segments has been successfully demonstrated. The "sourceless" nature of this technique makes possible full body posture tracking in an area of unlimited size with no supporting infrastructure. Such sensor modules contain three orthogonally mounted angular rate sensors, three orthogonal linear accelerometers and three orthogonal magnetometers. This paper describes a method for using accelerometer data combined with orientation estimates from the same modules to calculate position during walking and running. The periodic nature of these motions includes short periods of zero foot velocity when the foot is in contact with the ground. This pattern allows for precise drift error correction. Relative position is calculated through double integration of drift corrected accelerometer data. Preliminary experimental results for various types of motion including walking, side stepping, and running document accuracy of distance and position estimates.
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paper_title: A New Application for Transponders in Population Ecology of the Common Tern

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We injected transponders subcutaneously to mark single Common Tern (Sterna hirundo) adults and all chicks of a colony at Wilhelmshaven with the aim of establishing a completely marked colony. We present details on the equipment and methods and report preliminary results. Microtagged terns can be identified for life, not only at their nest when breeding, but also at resting places by fixed antennas at distances of < 11 cm. Thus, nonbreeders can be identified as well. We also weighed terns remotely to obtain information on their body condition. Body mass data as well as identification codes were electronically stored. Preliminary data indicated that adult survival was ≥ 87% and subadult survival until age two was ≥ 20%.
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paper_title: Seismic footstep signal characterization

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Seismic footstep detection based systems for homeland security applications are an important additional layer to perimeter protection and other security systems. This article reports seismic footstep signal characterization for different signal to noise ratios. Various footstep signal spectra are analyzed for different distances between a walking person and a seismic sensor. We also investigated kurtosis of the real footstep signals under various ::: environmental and modeled noises. We also report on the results of seismic signal summation from separate geophones. A seismic signal sum spectrum obtained was broader than that obtained from a single sensor. The peak of the seismic signal sum was broader than that from the footstep signal of the single sensor. The signal and noise ::: spectra have a greater overlap for a seismic signal sum than that from a single sensor. Generally, it is more difficult to filter out the noise from the sum of the seismic signals. We show that the use of the traditional approach of spectrum technology and/or the statistical characteristics of signal to noise of reliable footstep detection systems is not practical.
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paper_title: Tracking Long-Distance Songbird Migration by Using Geolocators

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We mapped migration routes of migratory songbirds to the Neotropics by using light-level geolocators mounted on breeding purple martins (Progne subis) and wood thrushes (Hylocichla mustelina). Wood thrushes from the same breeding population occupied winter territories within a narrow east-west band in Central America, suggesting high connectivity of breeding and wintering populations. Pace of spring migration was rapid (233 to 577 kilometers/day) except for one individual (159 kilometers/day) who took an overland route instead of crossing the Gulf of Mexico. Identifying songbird wintering areas and migration routes is critical for predicting demographic consequences of habitat loss and climate change in tropical regions.
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paper_title: RFID: a technical overview and its application to the enterprise

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Radio frequency identification (RFID) offers tantalizing benefits for supply chain management, inventory control, and many other applications. Only recently, however, has the convergence of lower cost and increased capabilities made businesses take a hard look at what RFID can do for them. This article offers an RFID tutorial that answers the following questions: i) what is RFID, and how does it work? ii) What are some applications of RFID? iii) What are some challenges and problems in RFID technology and implementation? iv) How have some organizations implemented RFID?.
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paper_title: Wireless sensor devices for animal tracking and control

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This paper describes some new wireless sensor hardware ::: developed for pastoral and environmental applications. ::: From our early experiments with Mote hardware we ::: were inspired to develop our devices with improved radio ::: range, solar power capability, mechanical and electrical robustness, ::: and with unique combinations of sensors. Here we ::: describe the design and evolution of a small family of devices: ::: radio/processor board, a soil moisture sensor interface, ::: and a single board multi-sensor unit for animal tracking ::: experiments.
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paper_title: The design and implementation of a self-calibrating distributed acoustic sensing platform

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We present the design, implementation, and evaluation of the Acoustic Embedded Networked Sensing Box (ENSBox), a platform for prototyping rapid-deployable distributed acoustic sensing systems, particularly distributed source localization. Each ENSBox integrates an ARM processor running Linux and supports key facilities required for source localization: a sensor array, wireless network services, time synchronization, and precise self-calibration of array position and orientation. The ENSBox’s integrated, high precision self-calibration facility sets it apart from other platforms. This self-calibration is precise enough to support acoustic source localization applications in complex, realistic environments: e.g., 5 cm average 2D position error and 1.5 degree average orientation error over a partially obstructed 80x50 m outdoor area. Further, our integration of array orientation into the position estimation algorithm is a novel extension of traditional multilateration techniques. We present the result of several different test deployments, measuring the performance of the system in urban settings, as well as forested, hilly environments with obstructing foliage and 20–30 m distances between neighboring nodes.
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paper_title: Evolution and sustainability of a wildlife monitoring sensor network

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As sensor network technologies become more mature, they are increasingly being applied to a wide variety of applications, ranging from agricultural sensing to cattle, oceanic and volcanic monitoring. Significant efforts have been made in deploying and testing sensor networks resulting in unprecedented sensing capabilities. A key challenge has become how to make these emerging wireless sensor networks more sustainable and easier to maintain over increasingly prolonged deployments. In this paper, we report the findings from a one year deployment of an automated wildlife monitoring system for analyzing the social co-location patterns of European badgers (Meles meles) residing in a dense woodland environment. We describe the stages of its evolution cycle, from implementation, deployment and testing, to various iterations of software optimization, followed by hardware enhancements, which in turn triggered the need for further software optimization. We report preliminary descriptive analyses of a subset of the data collected, demonstrating the significant potential our system has to generate new insights into badger behavior. The main lessons learned were: the need to factor in the maintenance costs while designing the system; to look carefully at software and hardware interactions; the importance of a rapid initial prototype deployment (this was key to our success); and the need for continuous interaction with domain scientists which allows for unexpected optimizations.
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paper_title: Geophone Detection of Subterranean Termite and Ant Activity

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A geophone system was used to monitor activity of subterranean termites and ants in a desert environment with low vibration noise. Examples of geophone signals were recorded from a colony of Rhytidoponera taurus (Forel), a colony of Camponotus denticulatus Kirby, and a termite colony (undetermined Drepanotermes sp.) under attack by ants from a nearby C. denticulatus colony. The geophone recordings were compared with signals recorded from accelerometers in a citrus grove containing Solenopsis invicta Buren workers. Because of their small size, all of these insects produce relatively weak sounds. Several different types of insect-generated sounds were identified in the geophone recordings, including high-frequency ticks produced by R. taurus and C. denticulatus, and patterned bursts of head bangs produced by Drepanotermes. The S. invicta produced bursts of ticks with three different stridulation frequencies, possibly produced by three different-sized workers. Overall, both systems performed well in enabling identification of high-frequency or patterned pulses. The geophone was more sensitive than the accelerometer to low-frequency signals, but low-frequency insect sound pulses are more difficult to distinguish from background noises than high-frequency pulses. The low cost of multiple-geophone systems may facilitate development of future applications for wide-area subterranean insect monitoring in quiet environments.
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paper_title: Lightweight Signal Processing Algorithms for Human Activity Monitoring using Dual PIR-sensor Nodes

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A dual Pyroelectric InfraRed (PIR) sensor node is ::: used for human activity monitoring by using simple data processing ::: techniques. We first point out the limitations of existing ::: approaches, employing PIR sensors, for activity monitoring. We ::: study the spectral characteristics of the sensor data for the cases ::: of varying distance between the sensor and moving object as well ::: as the speed of the object under observation. The sampled data ::: from two PIR sensors, is first processed individually to determine ::: the activity window size, which is then fed to a simple algorithm ::: to determine direction of motion.We also claim that human count ::: can be obtained for special scenarios. Preliminary results of our ::: experimentation show the effectiveness of the simple algorithm ::: proposed and give us an avenue for estimating more involved ::: parameters used for speed and localization.
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paper_title: Finding frequently visited paths: Dealing with the uncertainty of spatio-temporal mobility data

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With the ever-increasing advancements in sensor technology and localization systems, large amounts of spatio-temporal data can be collected from moving objects equipped with wireless sensor nodes. Analysis of such data provides the opportunity of extracting useful information about movement behaviour and interaction between moving objects. Inherent characteristics of wireless sensor nodes cause the data collected by them to have low or irregular frequency and often be erroneous. Existence of different levels of uncertainty in these data makes the procedure of finding movement patterns difficult and ambiguous. In this paper, we propose a hierarchical approach to find the frequently visited paths using location data of people carrying a custom designed mobile wireless sensor node. We hierarchically cluster trajectories and find their resemblance at the finest level while dealing with the uncertainties. The performance evaluation results show that compared with previous schemes, our method performs better in presence of ambiguity and sources of data uncertainty.
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paper_title: Towards radar-enabled sensor networks

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Ultra wideband radar-enabled wireless sensor networks have the potential to address key detection and classification requirements common to many surveillance and tracking applications. However, traditional radar signal processing techniques are mismatched with the limited computational and storage resources available on typical sensor nodes. The mismatch is exacerbated in noisy, cluttered environments or when the signals have corrupted spectra. To explore the compatibility of ultra wideband radar and mote-class sensor nodes, we designed and built a new platform called the radar mote. An early prototype of this platform was used to detect, classify, and track people and vehicles moving through an outdoor sensor network deployment. This paper describes the sensor's theory of operation, discusses the design and implementation of the radar mote, and presents sample signal waveforms of people, vehicles, noise, and clutter. We demonstrate that radar sensors can be successfully integrated with mote-class devices and imbue them with an extraordinarily useful sensing modality.
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paper_title: Acoustic monitoring in terrestrial environments using microphone arrays: applications, technological considerations and prospectus

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Summary 1. Animals produce sounds for diverse biological functions such as defending territories, attracting mates, deterring predators, navigation, finding food and maintaining contact with members of their social group. Biologists can take advantage of these acoustic behaviours to gain valuable insights into the spatial and temporal scales over which individuals and populations interact. Advances in bioacoustic technology, including the development of autonomous cabled and wireless recording arrays, permit data collection at multiple locations over time. These systems are transforming the way we study individuals and populations of animals and are leading to significant advances in our understandings of the complex interactions between animals and their habitats. 2. Here, we review questions that can be addressed using bioacoustic approaches, by providing a primer on technologies and approaches used to study animals at multiple organizational levels by ecologists, behaviourists and conservation biologists. 3. Spatially dispersed groups of microphones (arrays) enable users to study signal directionality on a small scale or to locate animals and track their movements on a larger scale. 4. Advances in algorithm development can allow users to discriminate among species, sexes, age groups and individuals. 5. With such technology, users can remotely and non-invasively survey populations, describe the soundscape, quantify anthropogenic noise, study species interactions, gain new insights into the social dynamics of sound-producing animals and track the effects of factors such as climate change and habitat fragmentation on phenology and biodiversity. 6. There remain many challenges in the use of acoustic monitoring, including the difficulties in performing signal recognition across taxa. The bioacoustics community should focus on developing a
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paper_title: A PIT tag based analysis of annual movement patterns of adult fire salamanders (Salamandra salamandra) in a Middle European habitat

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We studied patterns of annual movement of individual adult fire salamanders (Salamandra salamandra) during the years 2001 and 2002 in Western Germany in a typical middle European habitat for this species. We tested whether salamanders inhabit small home ranges and move little during the activity period as predicted for a species that shows strong site fidelity to a limited area. Initially, 98 individuals were collected in their natural habitat and marked with passive integrated transponder (PIT) tags. Of those individuals 88 were released at the collection site for recapture during the activity periods of the years 2001 and 2002. Ten marked individuals were kept in captivity to test for the tolerance of PIT tags. We did not find any negative impact of PIT tags on marked individuals of S. salamandra, neither under captive nor natural conditions. Forty-seven of the marked individuals (corresponding to 53% of the 88 released ones) were recaptured at least once and 28 individuals (corresponding to 32%) were recaptured multiple times. The return rate of males (78%) was higher than for females (43%). Mean home range size (and standard deviation) was estimated to 494 ± 282 m 2 for 4 individuals as the minimum convex polygon based on 5 to 6 recapture events for each individual per year and to 1295 ± 853 m 2 for 3 individuals with 8 records over two years. Minimum distances moved inferred from individual recaptures increased during the activity period of both years with time, indicating that individuals have more of a tendency to disperse than to stay within a limited area. Our data suggest therefore that S. salamandra adults display site fidelity, but use a much larger area than hitherto documented for this and other terrestrial salamander species.
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paper_title: Wireless sensor networks for habitat monitoring

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We provide an in-depth study of applying wireless sensor networks to real-world habitat monitoring. A set of system design requirements are developed that cover the hardware design of the nodes, the design of the sensor network, and the capabilities for remote data access and management. A system architecture is proposed to address these requirements for habitat monitoring in general, and an instance of the architecture for monitoring seabird nesting environment and behavior is presented. The currently deployed network consists of 32 nodes on a small island off the coast of Maine streaming useful live data onto the web. The application-driven design exercise serves to identify important areas of further work in data sampling, communications, network retasking, and health monitoring.
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paper_title: ZigBee-based wireless sensor networks for classifying the behaviour of a herd of animals using classification trees

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An in-depth study of wireless sensor networks applied to the monitoring of animal behaviour in the field is described. Herd motion data, such as the pitch angle of the neck and movement velocity, were monitored by an MTS310 sensor board equipped with a 2-axis accelerometer and received signal strength indicator functionality in a single-hop wireless sensor network. Pitch angle measurements and velocity estimates were transmitted through a wireless sensor network based on the ZigBee communication protocol. After data filtering, the pitch angle measurements together with velocity estimates were used to classify the animal behaviour into two classes; as activity and inactivity. Considering all the advantages and drawbacks of classification trees compared to neural network and fuzzy logic classifiers a general classification tree was preferred. The classification tree was constructed based on the measurements of the pitch angle of the neck and movement velocity of some animals in the herd and was used to predict the behaviour of other animals in the herd. The results showed that there was a large improvement in the classification accuracy if both the pitch angle of the neck and the velocity were employed as predictors when compared to just pitch angle or just velocity employed as a single predictor. The classification results showed the possibility of determining a general decision rule which can classify the behaviour of each individual in a herd of animals. The results were confirmed by manual registration and by GPS measurements.
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paper_title: Odor Recognition and Localization Using Sensor Networks

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Odor usually quantified by five parameters which are 1) intensity, 2) degree of offensiveness, 3) character, 4) frequency, and 5) duration. It has different forms including Gas, Chemical, Radiation, Organic Compounds, and Water odors including different water contaminations. For such odors, there are many of the traditional methods that have been used for a number of years. However, these methods suffer from different problems including the detection cost, the long time taken for analysis and detection, and exposing human to danger. On the other hand, the advances in sensing technology lead to the usage of sensor networks in many applications. For instance, sensors have been used to monitor animals in habitat areas and monitor patients’ health. In addition, sensor networks have been used to monitor critical infrastructures such as gas, transportation, energy, and water pipelines as well as important buildings. Sensors are tiny devices that can be included in small areas. At the same time, they are capable of capturing different phenomena from the environment, analyze the collected data, and take decisions. In addition, sensors are able to form unattended wireless ad hoc network that can survive for long time. Such features enable wireless sensor networks (WSN) to play an essential role in odor detection. In fact, odor detection became one of the important applications due to the terrorist attack that started by the one occurred at Tokyo Subway in 1995. Since this time, odor detection and localization is considered as one of the important applications. Researchers believe that sensors and sensor networks will play an important role in odor detection and localization. In this chapter, we generalize the term odor to include the radiation detection and localization since the radiation in most of the recent work is considered as an odor.
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paper_title: A prototype sensor node for footstep detection

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Persons moving over ground can be detected from vibrations induced to soil in the form of seismic waves which are measured by geophones or expensive MEMS accelerometers. We are proposing a sensor node that uses a low-cost bending mode piezoelectric accelerometer, operating near its resonant frequency, specially designed for footstep detection.
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paper_title: A Survey on Wireless Multimedia Sensor Networks

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The availability of low-cost hardware such as CMOS cameras and microphones has fostered the development of Wireless Multimedia Sensor Networks (WMSNs), i.e., networks of wirelessly interconnected devices that are able to ubiquitously retrieve multimedia content such as video and audio streams, still images, and scalar sensor data from the environment. In this paper, the state of the art in algorithms, protocols, and hardware for wireless multimedia sensor networks is surveyed, and open research issues are discussed in detail. Architectures for WMSNs are explored, along with their advantages and drawbacks. Currently off-the-shelf hardware as well as available research prototypes for WMSNs are listed and classified. Existing solutions and open research issues at the application, transport, network, link, and physical layers of the communication protocol stack are investigated, along with possible cross-layer synergies and optimizations.
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paper_title: SensEye: a multi-tier camera sensor network

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This paper argues that a camera sensor network containing heterogeneous elements provides numerous benefits over traditional homogeneous sensor networks. We present the design and implementation of senseye---a multi-tier network of heterogeneous wireless nodes and cameras. To demonstrate its benefits, we implement a surveillance application using senseye comprising three tasks: object detection, recognition and tracking. We propose novel mechanisms for low-power low-latency detection, low-latency wakeups, efficient recognition and tracking. Our techniques show that a multi-tier sensor network can reconcile the traditionally conflicting systems goals of latency and energy-efficiency. An experimental evaluation of our prototype shows that, when compared to a single-tier prototype, our multi-tier senseye can achieve an order of magnitude reduction in energy usage while providing comparable surveillance accuracy.
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paper_title: Acoustic and seismic modalities for unattended ground sensors

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In this paper, we have presented the relative advantages and complementary aspects of acoustic and seismic ground sensors. A detailed description of both acoustic and seismic ground sensing methods has been provided. Acoustic and seismic phenomenology including source mechanisms, propagation paths, attenuation, and sensing have been discussed in detail. The effects of seismo-acoustic and acousto-seismic interactions as well as recommendations for minimizing seismic/acoustic cross talk have been highlighted. We have shown representative acoustic and seismic ground sensor data to illustrate the advantages and complementary aspects of the two modalities. The data illustrate that seismic transducers often respond to acoustic excitation through acousto-seismic coupling. Based on these results, we discussed the implications of this phenomenology on the detection, identification, and localization objectives of unattended ground sensors. We have concluded with a methodology for selecting the preferred modality (acoustic and/or seismic) for a particular application.
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paper_title: RFID enhances visitors' museum experience at the Exploratorium

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Interactive RFID-enhanced museum exhibits let visitors continue their scientific exploration beyond the museum's walls. But museums must still help them understand the technology and address their data privacy concerns.
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paper_title: Human activity analysis: A review

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Human activity recognition is an important area of computer vision research. Its applications include surveillance systems, patient monitoring systems, and a variety of systems that involve interactions between persons and electronic devices such as human-computer interfaces. Most of these applications require an automated recognition of high-level activities, composed of multiple simple (or atomic) actions of persons. This article provides a detailed overview of various state-of-the-art research papers on human activity recognition. We discuss both the methodologies developed for simple human actions and those for high-level activities. An approach-based taxonomy is chosen that compares the advantages and limitations of each approach. Recognition methodologies for an analysis of the simple actions of a single person are first presented in the article. Space-time volume approaches and sequential approaches that represent and recognize activities directly from input images are discussed. Next, hierarchical recognition methodologies for high-level activities are presented and compared. Statistical approaches, syntactic approaches, and description-based approaches for hierarchical recognition are discussed in the article. In addition, we further discuss the papers on the recognition of human-object interactions and group activities. Public datasets designed for the evaluation of the recognition methodologies are illustrated in our article as well, comparing the methodologies' performances. This review will provide the impetus for future research in more productive areas.
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paper_title: Analysing Animal Behaviour in Wildlife Videos Using Face Detection and Tracking

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An algorithm that categorises animal locomotive behaviour by combining detection and tracking of animal faces in wildlife videos is presented. As an example, the algorithm is applied to lion faces. The detection algorithm is based on a human face detection method, utilising Haar-like features and AdaBoost classifiers. The face tracking is implemented by applying a specific interest model that combines low-level feature tracking with the detection algorithm. By combining the two methods in a specific tracking model, reliable and temporally coherent detection/tracking of animal faces is achieved. The information generated by the tracker is used to automatically annotate the animal's locomotive behaviour. The annotation classes of locomotive processes for a given animal species are predefined by a large semantic taxonomy on wildlife domain. The experimental results are presented.
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paper_title: Recognising human and animal movement by symmetry

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We show how the symmetry of motion can be extracted by using the generalised symmetry operator for analysing motion and for gait recognition. This operator, rather than relying on the borders of a shape or on general appearance, locates features by their symmetrical properties. This approach is reinforced by the view from psychology that human gait is a symmetrical pattern of motion, and by other works. We applied our new method to compare animal gait, and for recognition by gait. Results show that the symmetry properties of gait appear to be unique and can indeed be used for analysis and for recognition. We have so far achieved promising recognition rates of over 95%. Performance analysis also suggests that symmetry enjoys practical advantages such as relative immunity to noise with capability to handle occlusion and as such might prove suitable for applications like clip-database browsing.
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paper_title: Sensor Network for the Monitoring of Ecosystem: Bird Species Recognition

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In this paper, we investigated the performance of bird species recognition using neural networks with different preprocessing methods and different sets of features. Context neural network architecture was designed to embed the dynamic nature of bird songs into inputs. We devised a noise reduction algorithm and effectively applied it to enhance bird species recognition. The performance of the context neural network architecture was comparatively evaluated with linear/mel frequency cepstral coefficients and promising experimental results were achieved.
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paper_title: Human identification experiments using acoustic micro-Doppler signatures

paper_content:

Active acoustic scene analysis is a promising approach to distributed persistent surveillance in sensor networks. We report on the design of bandpass sampling technique for an acoustic micro-Doppler sonar to reduce the data rate to as low as 85 kbps. We then explore the use of Gaussian mixture models for human identification. We compare the classification performances using different feature vectors and from different sampling schemes. We show that the use of differential cepstral vectors of context length 2 improves the classification accuracy. We also show that the classification performance of the bandpass sampling system with an 8-bit resolution is still over 90% on a database consisting of 160 gait signatures from 8 individuals.
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paper_title: The Statistical Meaning of Kurtosis and Its New Application to Identification of Persons Based on Seismic Signals

paper_content:

This paper presents a new algorithm making use of kurtosis, which is a statistical parameter, to distinguish the seismic signal generated by a person's footsteps from other signals. It is adaptive to any environment and needs no machine study or training. As persons or other targets moving on the ground generate continuous signals in the form of seismic waves, we can separate different targets based on the seismic waves they generate. The parameter of kurtosis is sensitive to impulsive signals, so it's much more sensitive to the signal generated by person footsteps than other signals generated by vehicles, winds, noise, etc. The parameter of kurtosis is usually employed in the financial analysis, but rarely used in other fields. In this paper, we make use of kurtosis to distinguish person from other targets based on its different sensitivity to different signals. Simulation and application results show that this algorithm is very effective in distinguishing person from other targets.
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paper_title: Single- and three-axis geophone: footstep detection with bearing estimation, localization, and tracking

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Tactical capabilities of single and three axis geophones for seismic detection and bearing estimation for homeland security and defense applications are described. It is shown that typically three axis geophones yield a high bearing estimation error. An alternate bearing estimation approach is based on using the time delay in footstep signal detection from three triangulated single axis vertical geophones. In this approach the standard deviation of the bearing estimation error is less than 12 degrees for a walking person distance of 10 to 70m and geophone distances of 8 to 9 m. ::: ::: We find that using the three-axis geophone approach makes it harder for path tracking and bearing estimation within the tactical zone area. We report that a single-axis geophone approach for riangulation of walking person is more effective. In addition, road monitoring is also more efficient using a single-axis geophone approach. We compare ::: the relative and absolute improvement of bearing estimation probability for road monitoring using three single-axis geophones versus 1, 2 and 3 three-axis geophones. We will also discuss the use of single axis vertical geophone sets for monitoring various zone sizes.
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paper_title: Detecting Stink Bugs/Damage in Cotton Utilizing a Portable Electronic Nose

paper_content:

The goal of this study was to develop effective and affordable tools for detecting stink bugs ::: and stink bug induced damage in cotton production. A commercially available electronic nose ::: (Cyranose 320) was used for this purpose and its performance was evaluated under laboratory and ::: field conditions. The volatile compounds given off by stink bugs were identified to be trans-2-decenal ::: and trans-2-octenal. The E-nose was trained to identify stink bugs' (presence) smell prints. Only four ::: sensors, out of 32 available, responded to volatile chemicals produced by bugs. The same sensors ::: showed identical responses (smell prints) to trans-2-decenal as compared to those obtained from ::: sting bugs. Also, under laboratory conditions, the Cyranose accurately predicted damaged bolls, ::: interior walls of bolls and locks with lint and seed approximately 95 percent of the time. Under ::: laboratory conditions, the E-nose identified presence of stink bugs 100 percent of the time. There ::: was a strong correlation (R2 = 0.95) between the number of sting bugs in a sample and the ::: Cyranose sensors response. Under field conditions, the E-nose was able to identify stink bug ::: damaged bolls 67% of the time.
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paper_title: Gas-Chromatographic Analyses of the Subcaudal Gland Secretion of the European Badger (Meles meles) Part II: Time-Related Variation in the Individual-Specific Composition

paper_content:

Individuality in body odors has been described in a variety of species, but studies on time-related variation in individual scent are scarce. Here, we use GC-MS to investigate how chemical composition of subcaudal gland secretions of European badgers (Meles meles) varies over days, seasons, and from year to year, and how secretions change with the length of time for which they are exposed to the environment. Samples were divided into subsamples—one was frozen immediately and the remaining ones frozen after 2, 6, 12, 24, and 48 hr, respectively—and many individual-specific characteristics of the scent-profiles remained stable over time. However, two components were negatively correlated with time, thus providing the possibility to determine the age of scent marks. The low variation found in scent profiles of samples collected from the same individual three days apart showed that the individual-specific scent is a true characteristic of the respective badger, and that trapping and subsequent sampling have little effect on the composition of subcaudal gland secretions. Long-term variation (i.e., over one year) in individual subcaudal scent profiles is not continuous, but periods of relative stability are followed by periods of rapid change, that can be related to badger biology. Annual variation between samples collected from the same individuals in winter 1998 and winter 1999, and in spring 1998 and spring 1999 was lower than seasonal variation. Therefore, the results of this study indicate the potential of an individual-specific scent signature in the subcaudal gland secretions of badgers evidencing that individual recognition is of high importance in this species.
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paper_title: Footstep detection and tracking

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Persons or vehicles moving over ground generate a succession of impacts; these soil disturbances propagate away from the source as seismic waves. These seismic waves are especially useful in detecting footsteps which cannot be detected acoustically. Footstep signals can be distinguished from other seismic sources, such as vehicles or wind noise, by their impulsive nature. Even in noisy environments, statistical measures of the seismic amplitude distribution, such as kurtosis, can be used to identify a footstep. These detection methods can be used even with single component geophones. Moreover, the seismic signal is a vector wave that can be used to track the source bearing. To do such tracking a three-component measurement is needed. If multiple sources are separated in angle, we can use this bearing information to estimate the number of walkers.
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paper_title: Mammalian social odours: attraction and individual recognition

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Mammalian social systems rely on signals passed between individuals conveying information including sex, reproductive status, individual identity, ownership, competitive ability and health status. Many of these signals take the form of complex mixtures of molecules sensed by chemosensory systems and have important influences on a variety of behaviours that are vital for reproductive success, such as parent-offspring attachment, mate choice and territorial marking. This article aims to review the nature of these chemosensory cues and the neural pathways mediating their physiological and behavioural effects. Despite the complexities of mammalian societies, there are instances where single molecules can act as classical pheromones attracting interest and approach behaviour. Chemosignals with relatively high volatility can be used to signal at a distance and are sensed by the main olfactory system. Most mammals also possess a vomeronasal system, which is specialized to detect relatively non-volatile chemosensory cues following direct contact. Single attractant molecules are sensed by highly specific receptors using a labelled line pathway. These act alongside more complex mixtures of signals that are required to signal individual identity. There are multiple sources of such individuality chemosignals, based on the highly polymorphic genes of the major histocompatibility complex (MHC) or lipocalins such as the mouse major urinary proteins. The individual profile of volatile components that make up an individual odour signature can be sensed by the main olfactory system, as the pattern of activity across an array of broadly tuned receptor types. In addition, the vomeronasal system can respond highly selectively to non-volatile peptide ligands associated with the MHC, acting at the V2r class of vomeronasal receptor. The ability to recognize individuals or their genetic relatedness plays an important role in mammalian social behaviour. Thus robust systems for olfactory learning and recognition of chemosensory individuality have evolved, often associated with major life events, such as mating, parturition or neonatal development. These forms of learning share common features, such as increased noradrenaline evoked by somatosensory stimulation, which results in neural changes at the level of the olfactory bulb. In the main olfactory bulb, these changes are likely to refine the pattern of activity in response to the learned odour, enhancing its discrimination from those of similar odours. In the accessory olfactory bulb, memory formation is hypothesized to involve a selective inhibition, which disrupts the transmission of the learned chemosignal from the mating male. Information from the main olfactory and vomeronasal systems is integrated at the level of the corticomedial amygdala, which forms the most important pathway by which social odours mediate their behavioural and physiological effects. Recent evidence suggests that this region may also play an important role in the learning and recognition of social chemosignals.
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paper_title: An Electronic Nose Network System for Online Monitoring of Livestock Farm Odors

paper_content:

An electronic nose (e-nose)-based network system is developed for monitoring odors in and around livestock farms remotely. This network is built from compact e-noses that are tailored to measure odor compounds and environmental conditions such as temperature, wind speed, and humidity. The e-noses are placed at various applicable locations in and around the farm, and the collected odor data are transmitted via wireless network to a computer server, where the data processing algorithms process and analyze the data. The developed e-nose network system enables more effective odor management capabilities for more efficient operation of odor control practice by providing consistent, comprehensive, real-time data about the environment and odor profile in and around the livestock farms. Experimental and simulation results demonstrate the effectiveness of the developed system.
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paper_title: Identification of Stink Bugs Using an Electronic Nose

paper_content:

Abstract Stink bugs are recognized as pests of several economically important crops, including cotton, soybean and a variety of tree fruits. The Cyranose 320 was used for the classified investigation of stink bug. Stink bugs including males and females of the southern green stink bugs, Nezara viridula , were collected from crop fields around College Station, TX. Results show that the released chemicals and chemical intensity are both critical factors, which determine the rate that the Cyranose 320 correctly identified the stink bugs. The Cyranose 320 shows significant potential in identifying stink bugs, and can classify stink bug samples by species and gender.
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paper_title: Estimation of crowd behavior using sensor networks and sensor fusion

paper_content:

Commonly, surveillance operators are today monitoring a large number of CCTV screens, trying to solve the complex cognitive tasks of analyzing crowd behavior and detecting threats and other abnormal behavior. Information overload is a rule rather than an exception. Moreover, CCTV footage lacks important indicators revealing certain threats, and can also in other respects be complemented by data from other sensors. This article presents an approach to automatically interpret sensor data and estimate behaviors of groups of people in order to provide the operator with relevant warnings. We use data from distributed heterogeneous sensors (visual cameras and a thermal infrared camera), and process the sensor data using detection algorithms. The extracted features are fed into a Hidden Markov Model in order to model normal behavior and detect deviations. We also discuss the use of radars for weapon detection.
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paper_title: Spectrum analysis techniques for personnel detection using seismic sensors

paper_content:

There is a general need for improved detection range and false alarm performance for seismic sensors used for personnel detection. In this paper we describe a novel footstep detection algorithm which was developed and run on seismic footstep data collected at the Aberdeen Proving Ground in December 2000. The initial focus was an assessment of achievable detection range. The conventional approach to footstep detection is to detect transients corresponding to individual footfalls. We feel this is an error-prone approach. Because many real-world signals unrelated to human locomotion look like transients, transient-based footstep detection will inevitably either suffer from high false alarm rates or will be insensitive. Instead, we examined the use of spectrum analysis on envelope-detected seismic signals and have found the general method to be quite promising, not only for detection, but also for discrimination against other types of seismic sources. In particular, gait patterns and their corresponding signatures may help discriminate between human intruders and animals. In the APG data set, mean detection ranges of 64 meters (at P D =50%) were observed for normal walking, significantly improving on ranges previously reported. For running, mean detection ranges of 84 meters were observed. However, stealthy walking (creeping) remains a considerable problem. Even at short ranges (10 meters), in some cases the detection rate was less than 50%. In future efforts, additional data sets for a range of geologic and environmental conditions should be acquired and analyzed. Improvements to the detection algorithms are possible, including estimation of direction of travel and the number of intruders.
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paper_title: Acoustic Micro-Doppler Gait Signatures of Humans and Animals

paper_content:

A micro-Doppler active acoustic sensing system is described. We report its use in acquiring gait signatures of humans and four-legged animals in indoor and outdoor environments. Signals from an accelerometer attached to the leg support the interpretation of the components in the measured micro-Doppler signature. The acoustic micro-Doppler system described in this paper is simpler and offers advantages over the widely used electromagnetic wave micro-Doppler radars. It can be implemented in custom integrated circuits and embedded in a multi-modal wireless sensor network for autonomous detection and classification.
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paper_title: Radar micro-doppler for long range front-view gait recognition

paper_content:

We seek to understand the extraction of radar micro-Doppler signals generated by human motions at long range and with a front-view to use them as a biometric. We describe micro-Doppler algorithms used for the detection and tracking, and detail the gait features that can be extracted. We have measurements of multiple human subjects in outdoor but low-clutter backgrounds for identification and find that at long range and front-view, the probability of correct classification can be over 80%. However, the micro-Doppler signals are dependent on the direction of motion, and we discuss methods to reduce the effect of the direction of motion. These radar biometric features can serve as identifying features in a scene with multiple subjects. Ground truth using video and GPS is used to validate the radar data.
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paper_title: Geophone Detection of Subterranean Termite and Ant Activity

paper_content:

A geophone system was used to monitor activity of subterranean termites and ants in a desert environment with low vibration noise. Examples of geophone signals were recorded from a colony of Rhytidoponera taurus (Forel), a colony of Camponotus denticulatus Kirby, and a termite colony (undetermined Drepanotermes sp.) under attack by ants from a nearby C. denticulatus colony. The geophone recordings were compared with signals recorded from accelerometers in a citrus grove containing Solenopsis invicta Buren workers. Because of their small size, all of these insects produce relatively weak sounds. Several different types of insect-generated sounds were identified in the geophone recordings, including high-frequency ticks produced by R. taurus and C. denticulatus, and patterned bursts of head bangs produced by Drepanotermes. The S. invicta produced bursts of ticks with three different stridulation frequencies, possibly produced by three different-sized workers. Overall, both systems performed well in enabling identification of high-frequency or patterned pulses. The geophone was more sensitive than the accelerometer to low-frequency signals, but low-frequency insect sound pulses are more difficult to distinguish from background noises than high-frequency pulses. The low cost of multiple-geophone systems may facilitate development of future applications for wide-area subterranean insect monitoring in quiet environments.
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paper_title: Seismic signal transmission between burrows of the Cape mole-rat, Georychus capensis

paper_content:

Both seismic and auditory signals were tested for their propagation characteristics in a field study of the Cape mole-rat (Georychus capensis), a subterranean rodent in the family Bathyergidae. This solitary animal is entirely fossorial and apparently communicates with its conspecifics by alternately drumming its hind legs on the burrow floor. Signal production in this species is sexually dimorphic, and mate attraction is likely mediated primarily by seismic signalling between individuals in neighboring burrows. Measurements within, and at various distances away from, natural burrows suggest that seismic signals propagate at least an order of magnitude better than auditory signals. Moreover, using a mechanical thumper which could be triggered from a tape recording of the mole-rat's seismic signals, we established that the vertically-polarized surface wave (Rayleigh wave) propagates with less attenuation than either of the two horizontally-polarized waves. Thus, we tentatively hypothesize that Rayleigh waves subserve intraspecific communication in this species.
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paper_title: Acoustic monitoring in terrestrial environments using microphone arrays: applications, technological considerations and prospectus

paper_content:

Summary 1. Animals produce sounds for diverse biological functions such as defending territories, attracting mates, deterring predators, navigation, finding food and maintaining contact with members of their social group. Biologists can take advantage of these acoustic behaviours to gain valuable insights into the spatial and temporal scales over which individuals and populations interact. Advances in bioacoustic technology, including the development of autonomous cabled and wireless recording arrays, permit data collection at multiple locations over time. These systems are transforming the way we study individuals and populations of animals and are leading to significant advances in our understandings of the complex interactions between animals and their habitats. 2. Here, we review questions that can be addressed using bioacoustic approaches, by providing a primer on technologies and approaches used to study animals at multiple organizational levels by ecologists, behaviourists and conservation biologists. 3. Spatially dispersed groups of microphones (arrays) enable users to study signal directionality on a small scale or to locate animals and track their movements on a larger scale. 4. Advances in algorithm development can allow users to discriminate among species, sexes, age groups and individuals. 5. With such technology, users can remotely and non-invasively survey populations, describe the soundscape, quantify anthropogenic noise, study species interactions, gain new insights into the social dynamics of sound-producing animals and track the effects of factors such as climate change and habitat fragmentation on phenology and biodiversity. 6. There remain many challenges in the use of acoustic monitoring, including the difficulties in performing signal recognition across taxa. The bioacoustics community should focus on developing a
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paper_title: Acoustic backscattering by deepwater fish measured in situ from a manned submersible

paper_content:

An outstanding problem in fisheries acoustics is the depth dependence of scattering characteristics of swimbladderbearing fish, andthe effects of pressure on the target strength of physoclistous fish remain unresolved . In situ echoes from deepwater snappers were obtained with a sonar transducer mounted on a manned submersible next to a low-light video camera, permitting simultaneous echo recording and identification of species, fish size and orientation. The sonar system, consisting of a transducer, single board computer, hard disk, and analog-to-digital converter, used a 80ms, broadband signal (bandwidth 35 kHz, center frequency 120 kHz). The observed relationship between fish length and in situ target strength shows no difference from the relationship measured at the surface. No differences in the speciesspecific temporal echo characteristics were observedbetween surface andin situ measures. This ind icates that the size and shape of the snappers’ swimbladders are maintained both at the surface and at depths of up to 250 m. Information obtainedthrough controlledbackscatter measurements of tethered , anesthetizedfish at the surface can be appliedto free-swimming fish at depth. This is the first published account of the use of a manned submersible to measure in situ scattering from identified, individual animals with known orientations. The distinct advantage of this technique comparedwith other in situ techniques is the ability to observe the target fish, obtaining accurate species, size, and orientation information. r 2003 Elsevier Science Ltd. All rights reserved.
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paper_title: Application of Bioradiolocation for Estimation of the Laboratory Animals' Movement Activity

paper_content:

A method for estimation of the laboratory animals' movement activity by means of bioradar is proposed. The method could be used in time of zoo-psychological and pharmacological experiments. The experimental results for difierent states for the animal are presented. Speciflc features of frequency spectrums for these states are analyzed. Radiolocation of biological objects named as bioradiolocation is an intensively developing area of bio-medical engineering. There are some important medical tasks which could be applications flelds of radiolocation, among them are disaster medicine (searching of survivals under debris and rubbles of buildings), monitoring of breath and heart beating parameters for burned patients (it would cut down the number of used contact censors and thus decrease the risk of infection inoculation into burning wounds), sleep apnea diagnostics, monitoring of breath and heart beating parameters for sick persons, which are the carriers of extra-hazardous infections (it would decrease the risk of medical stafi infection), and etc (1,2). Besides the over listed flelds of application there is an interest in usage of bioradiolocation for remote diagnostics of rats and other laboratory animals by estimation of their moving activity in time of zoo-psychological and pharmacological experiments. At present, invasive methods of physiological parameters determination are used during testing of some medicine and poisonous substances on laboratory animals. Their moving activity used to be estimated visually by researcher. It could be pointed another method that is currently in use for animals' behavior reaction analysis. Specially designed video tracking system such as Ethovision (3) can be applied to decrease a workload of the researcher and create automatic approach to estimation of moving activity. The main disadvantage of this type of systems is necessity to use sophisticated software and some restriction on long time recording with duration more than several hours because of data storage capacity limitations. So, that is why in most cases estimation of rats' moving activity is carried out by researcher visually (4), which might cause in the quality of obtained information. Doppler radar has advantage of direct measurements of animal's moving parameters. It can be used for creation of a fully automatic moving activity integral estimation procedure. In this case the size of data is so small comparing to the video flle that it would allow to record data continuously during several days or more. Moreover in condition of creation special recognition algorithms of radar signals that were re∞ected from animal, it would be possible to discriminate difierent types of its movements (horizontal and vertical activities, grooming, steady state). In that case bioradiolocation can be also applied to data analysis of the open fleld experiments. Several experiments were carried out to investigate possibilities of laboratory animals' movement estimation by means of radar. These experiments and their results are given below. 2. EXPERIMENTAL INSTALLATION Multi-frequency radar with quadrature receiver designed at the Remote Sensing Laboratory was used in experiments with laboratory rats. The radar had following technical characteristics: Number of frequencies 16
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paper_title: Detection and Classification of Human Body Odor Using an Electronic Nose

paper_content:

An electronic nose (E-nose) has been designed and equipped with software that can detect and classify human armpit body odor. An array of metal oxide sensors was used for detecting volatile organic compounds. The measurement circuit employs a voltage divider resistor to measure the sensitivity of each sensor. This E-nose was controlled by in-house developed software through a portable USB data acquisition card with a principle component analysis (PCA) algorithm implemented for pattern recognition and classification. Because gas sensor sensitivity in the detection of armpit odor samples is affected by humidity, we propose a new method and algorithms combining hardware/software for the correction of the humidity noise. After the humidity correction, the E-nose showed the capability of detecting human body odor and distinguishing the body odors from two persons in a relative manner. The E-nose is still able to recognize people, even after application of deodorant. In conclusion, this is the first report of the application of an E-nose for armpit odor recognition.
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paper_title: INDIVIDUAL ACOUSTIC IDENTIFICATION AS A NON-INVASIVE CONSERVATION TOOL: AN APPROACH TO THE CONSERVATION OF THE AFRICAN WILD DOG LYCAON PICTUS (TEMMINCK, 1820)

paper_content:

ABSTRACT Individual variation in acoustic signals can be used for discrimination or identification purposes as a valuable supplement to radio-tagging and visual recognition. In this study, 721 hoo-calls from captive and free-ranging African wild dogs Lycaon pictus (n=9) were investigated for individual acoustic cues. The investigation applied a computer-aided sound analysis that allowed measurement of 93 parameters for each hoo-call. Discriminant function analyses demonstrated that the individuals differed in their call parameters primarily measured on the fundamental frequency. Additional discriminant analyses were run in order to find out if individuals can be re-identified once their hoo-calls are recorded and catalogued into a voice library. This procedure yielded an overall 67% correct assignment for the test data (ranging from 37% to 98% per individual), suggesting an above chance level re-recognition of individuals. The results establish the capability of re-identifying wild dogs using specific aco...
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paper_title: Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine

paper_content:

The feasibility of classifying different human activities based on micro-Doppler signatures is investigated. Measured data of 12 human subjects performing seven different activities are collected using a Doppler radar. The seven activities include running, walking, walking while holding a stick, crawling, boxing while moving forward, boxing while standing in place, and sitting still. Six features are extracted from the Doppler spectrogram. A support vector machine (SVM) is then trained using the measurement features to classify the activities. A multiclass classification is implemented using a decision-tree structure. Optimal parameters for the SVM are found through a fourfold cross-validation. The resulting classification accuracy is found to be more than 90%. The potentials of classifying human activities over extended time duration, through wall, and at oblique angles with respect to the radar are also investigated and discussed.
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paper_title: SEGMENTING QUADRUPED GAIT PATTERNS FROM WILDLIFE VIDEO

paper_content:

This paper describes a novel approach to detecting walking quadrupeds in unedited wildlife film footage. Variable lighting, moving backgrounds and camouflaged animals make traditional foreground extraction techniques such as optical flow and background subtraction unstable. We track a sparse set of points over a short film clip and use RANSAC to segment the foreground region. A novel technique, employing normalised convolution is then utilised to interpolate dense flow from the sparsely defined foreground. Dense flow is extracted for a number of clips demonstrating quadruped gait and other movements. Principal component analysis (PCA) is applied to this set of dense flows and eigenvectors not encapsulating periodic internal motion characteristics are disregarded. The projection coefficients for the remaining principal components are analysed as one dimensional time series. Projection coefficient variation reflects changes in the velocity and relative alignment of the components of the foreground object. These coefficients' relative phase differences are deduced using spectral analysis and degree of periodicity using dynamic time warping. These parameters are used to train a KNN classifier which segments the training data with 93% success rate. By generating projection coefficients for unseen footage, the system has successfully located examples of quadruped gait previously missed by human observers.
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paper_title: On the Detection of Footsteps Based on Acoustic and Seismic Sensing

paper_content:

In this work, we present a copula-based framework for integrating signals of different but statistically correlated modalities for binary hypothesis testing problems. Specifically, we consider the problem of detecting the presence of a human using footstep signals from seismic and acoustic sensors. An approach based on canonical correlation analysis and copula theory is employed to establish a likelihood ratio test. Experimental results based on real data are presented.
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paper_title: Application of wireless sensor system on security network

paper_content:

In this research we developed wireless sensor system for security application. We have used geophone to detect seismic ::: signals which are generated by footsteps. Geophones are resonant devices. Therefore, vibration on the land can generate ::: seismic waveforms which could be very similar to the signature by footstep. The signals from human footstep have weak ::: signals to noise ratio and the signal strength is subject to the distance between the sensor and human. In order to detect ::: weak signals from footstep, we designed and fabricated 2-stage amplification circuit which consists of active and RC ::: filters and amplifiers. The bandwidth of filter is 0.7Hz-150Hz and the gain of amplifier is set to 1000. The wireless ::: sensor system also developed to monitor the sensing signals at the remote place. The wireless sensor system consists of 3 ::: units; a wireless sensor unit, a wireless receiver unit, and a monitoring unit. The wireless sensor unit transmits amplified ::: signals from geophone with Zigbee, and the wireless receiver unit which has both Zigbee and Wi-Fi module receives ::: signals from the sensor unit and transmits signals to the monitoring system with Zigbee and Wi-Fi, respectively. By ::: using both Zigbee and Wi-Fi, the wireless sensor system can achieve the low power consumption and wide range ::: coverage.
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paper_title: Chemical characterization of volatile organic compounds on animal farms

paper_content:

More than one hundred volatile organic substances were identified by gas chromatography and mass spectrometry (GC/MS) in the indoor and outdoor air, stable and farm road dust and farm soil samples from two pig and cattle farms in the South Moravian Region. Volatile fatty acids (acetic, propanoic, butanoic and pentanoic acids) and their esters dominated along with aldehydes (butanal, pentanal and hexanal) and 4-methylphenol in the indoor and outdoor air samples. Road dust and soil samples contained mainly volatile aromatic compounds (toluene, benzene, ethylbenzene, styrene and xylenes), aliphatic hydrocarbons (largely n-alkanes), dichloromethane and carbon disulphide. The health risks associated with particular volatile compounds detected in the indoor and outdoor samples from the farms need to be assessed.
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paper_title: Synthesis of the pheromone-oriented behavior of silkworm moths by a mobile robot with moth antennae as pheromone sensors

paper_content:

The authors have studied the emergent mechanism in insect behavior by using a robotic system. Since insects have a simpler nervous system than humans, it is an appropriate model for clarifying the above mechanism. In this study, the pheromone oriented behavior of male silkworm moths was shown by a pheromone-guided mobile robot which had male moth antennae that can detect sex pheromones. This study focuses on the pheromone sensor that used antennae from a living moth. Since the antennae of silkworm moths are very sensitive as compared to artificial gas sensors, they can be used as living gas sensors that can detect pheromone molecules.
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paper_title: Detection of Multiple Heartbeats Using Doppler Radar

paper_content:

Doppler radar life sensing has shown promise in medical and security applications. The current paper considers the problem of determining the number of persons in a given area (e.g., a room) using the Doppler shift due to heartbeat. The signal is weak and time-varying, and therefore poses a complicated signal processing problem. We develop a generalized likelihood ratio test (GLRT) based on a model of the heartbeat, and show that this can be used to distinguish between the presence of 2, 1, or 0 subjects, even with a single antenna. We further extend this to N antennas. The results show that one can expect to detect up to 2N-1 subjects uartsing this technique.
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paper_title: Physiology-Based Face Recognition in the Thermal Infrared Spectrum

paper_content:

The current dominant approaches to face recognition rely on facial characteristics that are on or over the skin. Some of these characteristics have low permanency can be altered, and their phenomenology varies significantly with environmental factors (e.g., lighting). Many methodologies have been developed to address these problems to various degrees. However, the current framework of face recognition research has a potential weakness due to its very nature. We present a novel framework for face recognition based on physiological information. The motivation behind this effort is to capitalize on the permanency of innate characteristics that are under the skin. To establish feasibility, we propose a specific methodology to capture facial physiological patterns using the bioheat information contained in thermal imagery. First, the algorithm delineates the human face from the background using the Bayesian framework. Then, it localizes the superficial blood vessel network using image morphology. The extracted vascular network produces contour shapes that are characteristic to each individual. The branching points of the skeletonized vascular network are referred to as thermal minutia points (TMPs) and constitute the feature database. To render the method robust to facial pose variations, we collect for each subject to be stored in the database five different pose images (center, midleft profile, left profile, midright profile, and right profile). During the classification stage, the algorithm first estimates the pose of the test image. Then, it matches the local and global TMP structures extracted from the test image with those of the corresponding pose images in the database. We have conducted experiments on a multipose database of thermal facial images collected in our laboratory, as well as on the time-gap database of the University of Notre Dame. The good experimental results show that the proposed methodology has merit, especially with respect to the problem of low permanence over time. More importantly, the results demonstrate the feasibility of the physiological framework in face recognition and open the way for further methodological and experimental research in the area
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paper_title: METHODOLOGICAL INSIGHTS: Using seismic sensors to detect elephants and other large mammals: a potential census technique

paper_content:

Summary 1. Large mammal populations are difficult to census and monitor in remote areas. In particular, elephant populations in Central Africa are difficult to census due to dense forest, making aerial surveys impractical. Conservation management would be improved by a census technique that was accurate and precise, did not require large efforts in the field, and could record numbers of animals over a period of time. 2. We report a new detection technique that relies on sensing the footfalls of large mammals. A single geophone was used to record the footfalls of elephants and other large mammal species at a waterhole in Etosha National Park, Namibia. 3. Temporal patterning of footfalls is evident for some species, but this pattern is lost when there is more than one individual present. 4. We were able to discriminate between species using the spectral content of their footfalls with an 82% accuracy rate. 5. An estimate of the energy created by passing elephants (the area under the amplitude envelope) can be used to estimate the number of elephants passing the geophone. Our best regression line explained 55% of the variance in the data. This could be improved upon by using an array of geophones. 6. Synthesis and applications. This technique, when calibrated to specific sites, could be used to census elephants and other large terrestrial species that are difficult to count. It could also be used to monitor the temporal use of restricted resources, such as remote waterholes, by large terrestrial species.
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paper_title: Object tracking: A survey

paper_content:

The goal of this article is to review the state-of-the-art tracking methods, classify them into different categories, and identify new trends. Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns of both the object and the scene, nonrigid object structures, object-to-object and object-to-scene occlusions, and camera motion. Tracking is usually performed in the context of higher-level applications that require the location and/or shape of the object in every frame. Typically, assumptions are made to constrain the tracking problem in the context of a particular application. In this survey, we categorize the tracking methods on the basis of the object and motion representations used, provide detailed descriptions of representative methods in each category, and examine their pros and cons. Moreover, we discuss the important issues related to tracking including the use of appropriate image features, selection of motion models, and detection of objects.
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paper_title: Automatic identification of bird targets with radar via patterns produced by wing flapping

paper_content:

Bird identification with radar is important for bird migration research, environmental impact assessments (e.g. wind farms), aircraft security and radar meteorology. In a study on bird migration, radar signals from birds, insects and ground clutter were recorded. Signals from birds show a typical pattern due to wing flapping. The data were labelled by experts into the four classes BIRD, INSECT, CLUTTER and UFO (unidentifiable signals). We present a classification algorithm aimed at automatic recognition of bird targets. Variables related to signal intensity and wing flapping pattern were extracted (via continuous wavelet transform). We used support vector classifiers to build predictive models. We estimated classification performance via cross validation on four datasets. When data from the same dataset were used for training and testing the classifier, the classification performance was extremely to moderately high. When data from one dataset were used for training and the three remaining datasets were used as test sets, the performance was lower but still extremely to moderately high. This shows that the method generalizes well across different locations or times. Our method provides a substantial gain of time when birds must be identified in large collections of radar signals and it represents the first substantial step in developing a real time bird identification radar system. We provide some guidelines and ideas for future research.
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paper_title: Survey of gait recognition

paper_content:

Gait recognition, the process of identifying an individual by his /her walking style, is a relatively new research area. It has been receiving wide attention in the computer vision community. In this paper, a comprehensive survey of video based gait recognition approaches is presented. And the research challenges and future directions of the gait recognition are also discussed.
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paper_title: Footstep classification using wavelet decomposition

paper_content:

The characteristics of human footsteps are determined by the gait, the footwear and the floor. Accurate footstep analysis would be useful in various applications, home security service, surveillance and understanding of human action since the gait expresses personality, age and gender. The feasibility of personal identification has been confirmed by using the feature parameter of footsteps, however, it is necessary to use more effective parameters since the recognition rate of this method decreases as the number of subjects increases. In audio classification, Fourier and wavelet transform were used to extract the feature of audio signals. The feasibility of a footstep classification using Fourier and wavelet parameters were confirmed previously. In this paper, we focused on the wavelet parameter which consists of subband power, time-brightness and time-width. Previous work shows that the feature extraction using wavelet transform is effective for footstep categorizations, however, an optimal frame length for feature extraction and the relationship between a recognition rate and the length of feature parameters are not discussed in that paper. This paper provides two dominant results; the frame window size, which yield the good accuracy for footstep classification, is 4096; the feature parameter based on wavelet parameters can be reduced to 2/3 with equivalent recognition rate. Results show that the parameter applied herein yields effective and practical footstep classification.
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paper_title: Normal variation in thermal radiated temperature in cattle: implications for foot-and-mouth disease detection

paper_content:

BackgroundThermal imagers have been used in a number of disciplines to record animal surface temperatures and as a result detect temperature distributions and abnormalities requiring a particular course of action. Some work, with animals infected with foot-and-mouth disease virus, has suggested that the technique might be used to identify animals in the early stages of disease. In this study, images of 19 healthy cattle have been taken over an extended period to determine hoof and especially coronary band temperatures (a common site for the development of FMD lesions) and eye temperatures (as a surrogate for core body temperature) and to examine how these vary with time and ambient conditions.ResultsThe results showed that under UK conditions an animal's hoof temperature varied from 10°C to 36°C and was primarily influenced by the ambient temperature and the animal's activity immediately prior to measurement. Eye temperatures were not affected by ambient temperature and are a useful indicator of core body temperature.ConclusionsGiven the variation in temperature of the hooves of normal animals under various environmental conditions the use of a single threshold hoof temperature will be at best a modest predictive indicator of early FMD, even if ambient temperature is factored into the evaluation.
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paper_title: Analysis of human footsteps utilizing multi-axial seismic fusion

paper_content:

This paper introduces a method of enhancing an unattended ground sensor (UGS) system's classification capability of humans via seismic signatures while subsequently discriminating these events from a range of other sources of seismic activity. Previous studies have been performed to consistently discriminate between human and animal signatures using cadence analysis. The studies performed herein will expand upon this methodology by improving both the success rate of such methods as well as the effective range of classification. This is accomplished by fusing multiple seismic axes in real-time to separate impulsive events from environmental noise. Additionally, features can be extracted from the fused axes to gather more advanced information about the source of a seismic event. Compared to more basic cadence determination algorithms, the proposed method substantially improves the detection range and correct classification of humans and significantly decreases false classifications due to animals and ambient conditions.
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paper_title: What you see is not what you get: the role of ultrasonic detectors in increasing inventory completeness in Neotropical bat assemblages

paper_content:

Summary 1. Microchiropteran bats have the potential to be important biodiversity indicator species as they are distributed globally and are important in ecosystem functioning. Survey and monitoring protocols for bats are often ineffective as sampling techniques vary in their efficacy depending on the species involved and habitats surveyed. Acoustic sampling using bat detectors may prove an alternative or complementary technique to capture methods but is largely untested in the tropics. 2. To compare the efficacy of bat detectors and capture methods in surveys, we used ground mist nets, sub-canopy mist nets and harp traps to sample bats while simultaneously recording the echolocation calls of insectivorous bats in a diversity of habitats in the Yucatan, Mexico. We described echolocation calls, analysed call characteristics to identify species, and compared species inventories derived from traditional capture methods with those derived from acoustic sampling. 3. A total of 2819 bats representing 26 species and six families were captured; 83% were captured in ground nets, 13% in sub-canopy nets and 4% in harp traps. Fourteen species and five phonic types were identified based on five echolocation call characteristics. Discriminant function analysis showed a high level of correct classification of the calls (84·1%), indicating that identification of species by their echolocation calls is feasible. 4. In all habitats, acoustic sampling and capture methods sampled significantly more species each night than capture methods alone. Capture methods failed to sample 30% of the bat fauna, and aerial insectivores were sampled only by bat detectors. 5. Synthesis and applications . Given the importance of bats in ecosystem functioning, and their potential as indicator species, developing effective methodologies to survey and monitor bats is important for sustainable forest management and biodiversity conservation. Acoustic sampling should be used with capture methods to increase inventory completeness in bat assemblage studies, and could form part of a single standardized monitoring protocol that can be used globally in tropical forests, as this method detects aerial insectivores not sampled by capture methods.
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paper_title: Assessing the Use of Call Surveys to Monitor Breeding Anurans in Rhode Island

paper_content:

Our objective was to develop a long-term monitoring program that quantified anuran population trends in Rhode Island. Because road-based, manual call surveys are widely used in North America to monitor anurans, we assessed the efficacy of using this method to monitor the impact of anthropogenic change of anuran populations in the state. We quantified interspecific variation in calling chronology, calling frequency, and calling intensity at 31 breeding ponds in southern Rhode Island in 1998. Four distinct sampling periods were needed to monitor the seven species we detected. During a species' peak sampling period, males of some species called only sporadically within our 16-min surveys, such as pickerel frogs (Rana palustris), whereas other species called continually [spring peepers (Pseudacris crucifer) and green frogs (Rana clamitans)]. Based on accumulation curves, we suggest that call surveys in Rhode Island be conducted for 10-min at breeding ponds to have a high probability of detecting all species. Assuming we conduct one call survey annually during the four sampling periods, a power analysis estimated that we need to conduct 283 or 690 10-min surveys annually to detect 10% or 5% annual declines, respectively, to monitor most anurans in Rhode Island. Common species that are widespread and call frequently could be monitored with road-based call surveys. However, rarer species or those that call infrequently would be difficult to monitor with call surveys in Rhode Island; therefore other monitoring methods might be more appropriate.
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paper_title: Territorial dynamics of Mexican Ant-thrushes Formicarius moniliger revealed by individual recognition of their songs

paper_content:

The ability to monitor interactions between individuals over time can provide us with information on life histories, mating systems, behavioural interactions between individuals and ecological interactions with the environment. Tracking individuals over time has traditionally been a time- and often a cost-intensive exercise, and certain types of animals are particularly hard to monitor. Here we use canonical discriminant analysis (CDA) to identify individual Mexican Ant-thrushes using data extracted with a semi-automated procedure from song recordings. We test the ability of CDA to identify individuals over time, using recordings obtained over a 4-year period. CDA correctly identified songs of 12 individual birds 93.3% of the time from recordings in one year (2009), while including songs of 18 individuals as training data. Predicting singers in one year using recordings from other years indicated some instances of variation, with correct classification in the range of 67–88%; one individual was responsible for the great majority (66%) of classification errors. We produce temporal maps of the study plot showing that considerably more information was provided by identifying individuals from their songs than by ringing and re-sighting colour-ringed individuals. The spatial data show site fidelity in males, but medium-term pair bonds and an apparently large number of female floaters. Recordings can be used to monitor intra- and intersexual interactions of animals, their movements over time, their interactions with the environment and their population dynamics.
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paper_title: Tracking multiple animals in wildlife footage

paper_content:

We describe a method for tracking animals in wildlife footage. It uses a CONDENSATION particle filtering frame-work driven by learnt characteristics of specific animals. The key contribution is a periodic model of animal motion based on the relative positions over time of trackable features at significant body points. We also introduce techniques for maintaining a multimodal state density within the particle filter over time to enable consistent tracking of multiple animals. Initial experiments show that the approach has considerable potential.
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paper_title: New seismic unattended small size module for footstep and light and heavy vehicles detection and identification

paper_content:

General Sensing Systems (GSS) has developed a new seismic, unattended small size module that detects and identifies not only human footsteps but also light and heavy vehicles with near zero false alarm rates. This module has extremely low power consumption and can operate for several months using standard commercial batteries. This paper describes the design of this module that can communicate with any radio transducer or computer. We also report on the preliminary lab and field testing that was implemented in various environment conditions. We show that the new unattended, small size detection module demonstrates the same reliable performance as our previous footstep detection systems and has the added capability of detecting and identifying light and heavy vehicles.
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paper_title: Biometric animal databases from field photographs: identification of individual zebra in the wild

paper_content:

We describe an algorithmic and experimental approach to a fundamental problem in field ecology: computer-assisted individual animal identification. We use a database of noisy photographs taken in the wild to build a biometric database of individual animals differentiated by their coat markings. A new image of an unknown animal can then be queried by its coat markings against the database to determine if the animal has been observed and identified before. Our algorithm, called StripeCodes, efficiently extracts simple image features and uses a dynamic programming algorithm to compare images. We test its accuracy against two different classes of methods: Eigenface, which is based on algebraic techniques, and matching multi-scale histograms of differential image features, an approach from signal processing. StripeCodes performs better than all competing methods for our dataset, and scales well with database size.
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paper_title: Bird migration flight altitudes studied by a network of operational weather radars

paper_content:

A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which—when extended to multiple radars—enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe.
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paper_title: Application of remote thermal imaging and night vision technology to improve endangered wildlife resource management with minimal animal distress and hazard to humans

paper_content:

Advanced electromagnetic sensor systems more commonly associated with the hightech military battlefield may be applied to remote surveillance of wildlife. The first comprehensive study of a wide global variety of Near Infra Red (NIR) and thermal wildlife portraits are presented with this technology: for mammals, birds and other animals. The paper illustrates the safety aspects afforded to zoo staff and personnel in the wild during the day and night from potentially lethal and aggressive animals, and those difficult to approach normally. Such remote sensing systems are non-invasive and provide minimal disruption and distress to animals both in captivity and in the wild. We present some of the veterinarian advantages of such all weather day and night systems to identify sickness and injuries at an early diagnostic stage, as well as age related effects and mammalian cancer. Animals have very different textured surfaces, reflective and emissive properties in the NIR and thermal bands than when compared with the visible spectrum. Some surface features may offer biomimetic materials design advantages.
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paper_title: Evaluation of unpleasant odor with a portable electronic nose

paper_content:

An intelligent multi-sensor system with an entire autonomy, a low weight and a small size has been developed for in situ applications such as environmental pollutant gas detection or olfactory estimation. This portable electronic nose works with commercial metal oxide gas sensors and a microcontroller connected to a compact flash memory as intelligent unit. In this work we present the conception of this electronic nose, its laboratory validation, and a real application which concerns an outdoor air monitoring of a duck breeding. This application is developed in order to quantify continuously discomfort odor spread, causing neighbor complaints. The odor measurements were made using our electronic nose (Nepo) and results are compared to the simultaneous results obtained from other olfactometric techniques.
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paper_title: A line in the sand: A wireless sensor network for target detection, classification, and tracking

paper_content:

Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a dense, distributed, wireless network of multi-modal resource-poor sensors combined into loosely coherent sensor arrays that perform in situ detection, estimation, compression, and exfiltration. We ground our study in the context of a security scenario called "A Line in the Sand" and accordingly define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking, and middleware services. We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of our work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effects of network unreliability on application performance. Our work includes multiple experimental deployments of over 90 sensor nodes at MacDill Air Force Base in Tampa, FL, as well as other field experiments of comparable scale. Based on these experiences, we identify a set of key lessons and articulate a few of the challenges facing extreme scaling to tens or hundreds of thousands of sensor nodes.
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paper_title: Cadence analysis of temporal gait patterns for seismic discrimination between human and quadruped footsteps

paper_content:

This paper reports on a method of cadence analysis for the discrimination between human and quadruped using a cheap seismic sensor. Previous works in the domain of seismic detection of human vs. quadruped have relied on the fundamental gait frequency. Slow movement of quadrupeds can generate the same fundamental gait frequency as human footsteps therefore causing the recognizer to be confused when quadruped are ambling around the sensor. Here we propose utilizing the cadence analysis of temporal gait pattern which provides information on temporal distribution of the gait beats. We also propose a robust method of extracting temporal gait patterns. Features extracted from gait patterns are modeled with optimum number of Gaussian Mixture Models (GMMs). The performance of the system during the test for discriminating between horse, dog, multiple people walk, and single human walk/run was over 95%.
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paper_title: The Cow Gait Recognition Using CHLAC

paper_content:

This paper reports the preliminary experiments on the cow identification via gait recognition of motion images. The eight cows walking under two different situations have been precisely identified by Cubic Higher-order Local Auto-Correlation (CHLAC). The cow gait recognition using CHLAC is expected to be a landmark achievement for realizing cost-effective dairy cattle breeding management systems which do not use any sensors and hormone in order to determine the timing of artificial insemination in dairy cattle.
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paper_title: Improved human detection and classification in thermal images

paper_content:

We present a new method for detecting pedestrians in thermal images. The method is based on the Shape Context Descriptor (SCD) with the Adaboost cascade classifier framework. Compared with standard optical images, thermal imaging cameras offer a clear advantage for night-time video surveillance. It is robust on the light changes in day-time. Experiments show that shape context features with boosting classification provide a significant improvement on human detection in thermal images. In this work, we have also compared our proposed method with rectangle features on the public dataset of thermal imagery [1]. Results show that shape context features are much better than the conventional rectangular features on this task.
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paper_title: Insect pheromones.

paper_content:

The evidence for intraspecies chemical communication in insects is reviewed, with emphasis on those studies where known organic compounds have been implicated. These signal-carrying chemicals are known as pheromones. There are two distinct types of pheromones, releasers and primers. Releaser pheromones initiate immediate behavioral responses in insects upon reception, while primer pheromones cause physiological changes in an animal that ultimately result in a behavior response. Chemically identified releaser pheromones are of three basic types: those which cause sexual attraction, alarm behavior, and recruitment. Sex pheromones release the entire repertoire of sexual behavior. Thus a male insect may be attracted to and attempt to copulate with an inanimate object that has sex pheromone on it. It appears that most insects are rather sensitive and selective for the sex pheromone of their species. Insects show far less sensitivity and chemospecificity for alarm pheromones. Alarm selectivity is based more on volatility than on unique structural features. Recruiting pheromones are used primarily in marking trails to food sources. Terrestrial insects lay continuous odor trails, whereas bees and other airborne insects apply the substances at discrete intervals. It appears that a complex pheromone system is used by the queen bee in the control of worker behavior. One well-established component of this system is a fatty acid, 9-ketodecenoic acid, produced by the queen and distributed among the workers. This compound prevents the development of ovaries in the workers and inhibits their queen-rearing activities. In addition, the same compound is used by virgin queen bees as a sex attractant.
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paper_title: Acoustic monitoring in terrestrial environments using microphone arrays: applications, technological considerations and prospectus

paper_content:

Summary 1. Animals produce sounds for diverse biological functions such as defending territories, attracting mates, deterring predators, navigation, finding food and maintaining contact with members of their social group. Biologists can take advantage of these acoustic behaviours to gain valuable insights into the spatial and temporal scales over which individuals and populations interact. Advances in bioacoustic technology, including the development of autonomous cabled and wireless recording arrays, permit data collection at multiple locations over time. These systems are transforming the way we study individuals and populations of animals and are leading to significant advances in our understandings of the complex interactions between animals and their habitats. 2. Here, we review questions that can be addressed using bioacoustic approaches, by providing a primer on technologies and approaches used to study animals at multiple organizational levels by ecologists, behaviourists and conservation biologists. 3. Spatially dispersed groups of microphones (arrays) enable users to study signal directionality on a small scale or to locate animals and track their movements on a larger scale. 4. Advances in algorithm development can allow users to discriminate among species, sexes, age groups and individuals. 5. With such technology, users can remotely and non-invasively survey populations, describe the soundscape, quantify anthropogenic noise, study species interactions, gain new insights into the social dynamics of sound-producing animals and track the effects of factors such as climate change and habitat fragmentation on phenology and biodiversity. 6. There remain many challenges in the use of acoustic monitoring, including the difficulties in performing signal recognition across taxa. The bioacoustics community should focus on developing a
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paper_title: Recognition of moving ground targets by measuring and processing seismic signal

paper_content:

Abstract Because vehicles moving over ground generate a succession of impacts, the soil disturbances propagate away from the source as seismic waves. Thus, in the battlefield environment, we can detect moving ground vehicles by means of measuring seismic signals using a seismic velocity transducer, and automatically classify and recognize them by advance signal processing method. Because seismic sensor is easy to be developed by emerging micro-electro-mechanical system (MEMS) technology, seismic detection that will be low cost, low power, small volume and light weight is a promising method for moving ground targets. Such a detection method can be used in many different fields, such as battlefield surveillance, traffic monitoring, law enforcement and so on. The paper researches seismic signals of typical vehicle targets in order to extract features of seismic signal and to recognize targets. As a data fusion method, the technique of artificial neural networks (ANN) is applied to recognize seismic signals for vehicle targets. An improved BP algorithm and ANN data fusion architecture have been presented to improve learning speed and avoid local minimum points in error curve. The algorithm had been used for classification and recognition of seismic signals of vehicle targets in the outdoor environment. It can be proven that moving ground vehicles can be detected by measuring seismic signal, feature extraction of target seismic signal is correct and ANN data fusion is effective to solve the recognition and classification problem for moving ground targets.
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paper_title: Acoustic and seismic modalities for unattended ground sensors

paper_content:

In this paper, we have presented the relative advantages and complementary aspects of acoustic and seismic ground sensors. A detailed description of both acoustic and seismic ground sensing methods has been provided. Acoustic and seismic phenomenology including source mechanisms, propagation paths, attenuation, and sensing have been discussed in detail. The effects of seismo-acoustic and acousto-seismic interactions as well as recommendations for minimizing seismic/acoustic cross talk have been highlighted. We have shown representative acoustic and seismic ground sensor data to illustrate the advantages and complementary aspects of the two modalities. The data illustrate that seismic transducers often respond to acoustic excitation through acousto-seismic coupling. Based on these results, we discussed the implications of this phenomenology on the detection, identification, and localization objectives of unattended ground sensors. We have concluded with a methodology for selecting the preferred modality (acoustic and/or seismic) for a particular application.
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paper_title: Cadence analysis of temporal gait patterns for seismic discrimination between human and quadruped footsteps

paper_content:

This paper reports on a method of cadence analysis for the discrimination between human and quadruped using a cheap seismic sensor. Previous works in the domain of seismic detection of human vs. quadruped have relied on the fundamental gait frequency. Slow movement of quadrupeds can generate the same fundamental gait frequency as human footsteps therefore causing the recognizer to be confused when quadruped are ambling around the sensor. Here we propose utilizing the cadence analysis of temporal gait pattern which provides information on temporal distribution of the gait beats. We also propose a robust method of extracting temporal gait patterns. Features extracted from gait patterns are modeled with optimum number of Gaussian Mixture Models (GMMs). The performance of the system during the test for discriminating between horse, dog, multiple people walk, and single human walk/run was over 95%.
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paper_title: SEGMENTING QUADRUPED GAIT PATTERNS FROM WILDLIFE VIDEO

paper_content:

This paper describes a novel approach to detecting walking quadrupeds in unedited wildlife film footage. Variable lighting, moving backgrounds and camouflaged animals make traditional foreground extraction techniques such as optical flow and background subtraction unstable. We track a sparse set of points over a short film clip and use RANSAC to segment the foreground region. A novel technique, employing normalised convolution is then utilised to interpolate dense flow from the sparsely defined foreground. Dense flow is extracted for a number of clips demonstrating quadruped gait and other movements. Principal component analysis (PCA) is applied to this set of dense flows and eigenvectors not encapsulating periodic internal motion characteristics are disregarded. The projection coefficients for the remaining principal components are analysed as one dimensional time series. Projection coefficient variation reflects changes in the velocity and relative alignment of the components of the foreground object. These coefficients' relative phase differences are deduced using spectral analysis and degree of periodicity using dynamic time warping. These parameters are used to train a KNN classifier which segments the training data with 93% success rate. By generating projection coefficients for unseen footage, the system has successfully located examples of quadruped gait previously missed by human observers.
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paper_title: Do ants make direct comparisons?

paper_content:

Many individual decisions are informed by direct comparison of the alternatives. In collective decisions, however, only certain group members may have the opportunity to compare options. Emigrating ant colonies (Temnothorax albipennis) show sophisticated nest-site choice, selecting superior sites even when they are nine times further away than the alternative. How do they do this? We used radio-frequency identification-tagged ants to monitor individual behaviour. Here we show for the first time that switching between nests during the decision process can influence nest choice without requiring direct comparison of nests. Ants finding the poor nest were likely to switch and find the good nest, whereas ants finding the good nest were more likely to stay committed to that nest. When ants switched quickly between the two nests, colonies chose the good nest. Switching by ants that had the opportunity to compare nests had little effect on nest choice. We suggest a new mechanism of collective nest choice: individuals respond to nest quality by the decision either to commit or to seek alternatives. Previously proposed mechanisms, recruitment latency and nest comparison, can be explained as side effects of this simple rule. Colony-level comparison and choice can emerge, without direct comparison by individuals.
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paper_title: Evolution and sustainability of a wildlife monitoring sensor network

paper_content:

As sensor network technologies become more mature, they are increasingly being applied to a wide variety of applications, ranging from agricultural sensing to cattle, oceanic and volcanic monitoring. Significant efforts have been made in deploying and testing sensor networks resulting in unprecedented sensing capabilities. A key challenge has become how to make these emerging wireless sensor networks more sustainable and easier to maintain over increasingly prolonged deployments. In this paper, we report the findings from a one year deployment of an automated wildlife monitoring system for analyzing the social co-location patterns of European badgers (Meles meles) residing in a dense woodland environment. We describe the stages of its evolution cycle, from implementation, deployment and testing, to various iterations of software optimization, followed by hardware enhancements, which in turn triggered the need for further software optimization. We report preliminary descriptive analyses of a subset of the data collected, demonstrating the significant potential our system has to generate new insights into badger behavior. The main lessons learned were: the need to factor in the maintenance costs while designing the system; to look carefully at software and hardware interactions; the importance of a rapid initial prototype deployment (this was key to our success); and the need for continuous interaction with domain scientists which allows for unexpected optimizations.
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paper_title: CARNIVORE: a disruption-tolerant system for studying wildlife

paper_content:

We present CARNIVORE, a system for in situ, unobtrusive monitoring of cryptic, difficult-to-catch/observe wildlife in their natural habitat. CARNIVORE is a network of mobile and static nodes with sensing, processing, storage, and wireless communication capabilities. CARNIVORE's compact, low-power, mobile animal-borne nodes collect sensor data and transmit it to static nodes, which then relay it to the Internet. Depending on the wildlife being studied, the network can be quite sparse and therefore disconnected frequently for arbitrarily long periods of time. To support "disconnected operation", CARNIVORE uses an "opportunistic routing" approach taking advantage of every encounter between nodes (mobile-to-mobile and mobile-to-static) to propagate data. With a lifespan of 50-100 days, a CARNIVORE mobile node, outfitted on a collar, collects and transmits 1 GB of data compared to 450 kB of data from comparable commercially available wildlife collars. Each collar records 3-axis accelerometer and GPS data to infer animal behavior and energy consumption.Testing in both laboratory and free-range settings with domestic dogs shows that galloping and trotting behavior can be identified. Data collected fromfirst deployments on mountain lions (Puma concolor) near Santa Cruz, CA, USA show that the system is a viable and useful tool for wildlife research.
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paper_title: Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

paper_content:

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.
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paper_title: Rapid Prototyping for Wildlife and Ecological Monitoring

paper_content:

Wildlife tracking and ecological monitoring are important for scientific monitoring, wildlife rehabilitation, disease control, and sustainable ecological development. Yet technologies for both of them are expensive and not scalable. Also it is important to tune the monitoring system parameters for different species to adapt their behavior and gain the best result of monitoring. In this paper, we propose using wireless sensor networks to build both short term and long term wildlife and ecological monitoring systems. For the short term system, everything used is off-the-shelf and can be easily purchased from the market. We suggest that before establishing a large scale wildlife/ecological monitoring network, it is worthwhile to first spend a short period of time constructing a rapid prototype of the targeted network. Through verifying the correctness of the prototype network, ecologists can find potential problems, avoid total system failure, and use the best-tuned parameters for the long-term monitoring network.
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paper_title: Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet

paper_content:

Over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. The field of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices for both scientific and commercial purposes. This paper examines the research decisions and design tradeoffs that arise when applying wireless peer-to-peer networking techniques in a mobile sensor network designed to support wildlife tracking for biology research.The ZebraNet system includes custom tracking collars (nodes) carried by animals under study across a large, wild area; the collars operate as a peer-to-peer network to deliver logged data back to researchers. The collars include global positioning system (GPS), Flash memory, wireless transceivers, and a small CPU; essentially each node is a small, wireless computing device. Since there is no cellular service or broadcast communication covering the region where animals are studied, ad hoc, peer-to-peer routing is needed. Although numerous ad hoc protocols exist, additional challenges arise because the researchers themselves are mobile and thus there is no fixed base station towards which to aim data. Overall, our goal is to use the least energy, storage, and other resources necessary to maintain a reliable system with a very high `data homing' success rate. We plan to deploy a 30-node ZebraNet system at the Mpala Research Centre in central Kenya. More broadly, we believe that the domain-centric protocols and energy tradeoffs presented here for ZebraNet will have general applicability in other wireless and sensor applications.
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paper_title: Animal Behaviour Understanding using Wireless Sensor Networks

paper_content:

This paper presents research that is being conducted by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) with the aim of investigating the use of wireless sensor networks for automated livestock monitoring and control. It is difficult to achieve practical and reliable cattle monitoring with current conventional technologies due to challenges such as large grazing areas of cattle, long time periods of data sampling, and constantly varying physical environments. Wireless sensor networks bring a new level of possibilities into this area with the potential for greatly increased spatial and temporal resolution of measurement data. CSIRO has created a wireless sensor platform for animal behaviour monitoring where we are able to observe and collect information of animals without significantly interfering with them. Based on such monitoring information, we can identify each animal's behaviour and activities successfully
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paper_title: Wireless indoor tracking network based on Kalman filters with an application to monitoring dairy cows

paper_content:

We propose an algorithm for estimating positions of devices in a sensor network using Kalman filtering techniques. The specific area of application is monitoring the movements of cows in a barn. The algorithm consists of two filters. The first filter enhances the signal-to-noise ratio of the observed signal strengths and gives interpolated values at specific timestamps. Information from the first filter is transferred to the second filter which estimates the positions. Methods for estimating the parameters of the filters are given and these provide a straightforward calibration of the system.
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paper_title: Identification of animal movement patterns using tri-axial accelerometry

paper_content:

An animal's behaviour is a response to its environment and physiological condition, and as such, gives vital clues as to its well-being, which is highly relevant in conservation issues. Behav- iour can generally be typified by body motion and body posture, parameters that are both measurable using animal-attached accelerometers. Interpretation of acceleration data, however, can be complex, as the static (indicative of posture) and dynamic (motion) components are derived from the total acceleration values, which should ideally be recorded in all 3-dimensional axes. The principles of tri- axial accelerometry are summarised and discussed in terms of the commonalities that arise in pat- terns of acceleration across species that vary in body pattern, life-history strategy, and the medium they inhabit. Using tri-axial acceleration data from deployments on captive and free-living animals (n = 12 species), behaviours were identified that varied in complexity, from the rhythmic patterns of locomotion, to feeding, and more variable patterns including those relating to social interactions. These data can be combined with positional information to qualify patterns of area-use and map the distribution of target behaviours. The range and distribution of behaviour may also provide insight into the transmission of disease. In this way, the measurement of tri-axial acceleration can provide insight into individual and population level processes, which may ultimately influence the effective- ness of conservation practice.
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paper_title: Smart sensors for small rodent observation

paper_content:

Working towards the observation of rats (and other small rodents) in the wild we have developed tools that will enable us to study their behavior using a wireless network of wearable sensor nodes. The space and weight constraints resulting from the size of the animals have led to simple but functional approaches for vocalization classification and position estimation. For the resulting data we have developed novel, delay-tolerant routing and collection strategies. These are expected to be used in a sparse, dynamic network resulting from various rats being tagged with our nodes and running around freely - an area that will eventually be too big to be covered solely by stationary data sinks. Furthermore, the system is designed to extract information on the social interactions between animals from the routing data. It currently works in an indoor environment and we are preparing it for tests in a controlled outdoor setup.
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paper_title: ZigBee-based wireless sensor networks for classifying the behaviour of a herd of animals using classification trees

paper_content:

An in-depth study of wireless sensor networks applied to the monitoring of animal behaviour in the field is described. Herd motion data, such as the pitch angle of the neck and movement velocity, were monitored by an MTS310 sensor board equipped with a 2-axis accelerometer and received signal strength indicator functionality in a single-hop wireless sensor network. Pitch angle measurements and velocity estimates were transmitted through a wireless sensor network based on the ZigBee communication protocol. After data filtering, the pitch angle measurements together with velocity estimates were used to classify the animal behaviour into two classes; as activity and inactivity. Considering all the advantages and drawbacks of classification trees compared to neural network and fuzzy logic classifiers a general classification tree was preferred. The classification tree was constructed based on the measurements of the pitch angle of the neck and movement velocity of some animals in the herd and was used to predict the behaviour of other animals in the herd. The results showed that there was a large improvement in the classification accuracy if both the pitch angle of the neck and the velocity were employed as predictors when compared to just pitch angle or just velocity employed as a single predictor. The classification results showed the possibility of determining a general decision rule which can classify the behaviour of each individual in a herd of animals. The results were confirmed by manual registration and by GPS measurements.
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paper_title: Activity recognition from user-annotated acceleration data

paper_content:

In this work, algorithms are developed and evaluated to de- tect physical activities from data acquired using five small biaxial ac- celerometers worn simultaneously on different parts of the body. Ac- celeration data was collected from 20 subjects without researcher su- pervision or observation. Subjects were asked to perform a sequence of everyday tasks but not told specifically where or how to do them. Mean, energy, frequency-domain entropy, and correlation of acceleration data was calculated and several classifiers using these features were tested. De- cision tree classifiers showed the best performance recognizing everyday activities with an overall accuracy rate of 84%. The results show that although some activities are recognized well with subject-independent training data, others appear to require subject-specific training data. The results suggest that multiple accelerometers aid in recognition because conjunctions in acceleration feature values can effectively discriminate many activities. With just two biaxial accelerometers - thigh and wrist - the recognition performance dropped only slightly. This is the first work to investigate performance of recognition algorithms with multiple, wire-free accelerometers on 20 activities using datasets annotated by the subjects themselves.
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Title: Sensing Solutions for Collecting Spatio-Temporal Data for Wildlife Monitoring Applications: A Review

Section 1: Introduction
Description 1: Write about the importance of animal movement in ecological processes and the challenges of traditional data collection methods.

Section 2: Classification of Technologies for Collecting Spatio-Temporal Data
Description 2: Explain the two main approaches (Lagrangian and Eulerian) for collecting spatio-temporal data, and the classification of technologies based on these approaches.

Section 3: Technologies for Eulerian Approach
Description 3: Discuss the technologies utilized for the Eulerian approach, including their modalities, sensors, and data analysis techniques.

Section 4: Echoes as a Modality
Description 4: Detail the use of radar, sonar, and lidar technologies inspired by animals like bats and dolphins that use echolocation.

Section 5: Visual Modality
Description 5: Describe how visual data from cameras can be used to identify and track animals, focusing on visual interpretation methods.

Section 6: Thermal Sensors (Thermal Receptors)
Description 6: Discuss the use of thermal sensors to detect animals based on their infrared radiation and thermal hotspots.

Section 7: Chemical Modality
Description 7: Explore the use of chemical sensors (electronic noses) for identifying animals based on volatile organic compounds they emit.

Section 8: Microphones (Acoustic Receptors)
Description 8: Explain the use of microphones to detect and identify animals through their vocal sounds and incidental noises.

Section 9: Seismic Modality
Description 9: Discuss the detection of animals through seismic waves produced by their movements, particularly footsteps.

Section 10: Technologies for the Lagrangian Approach
Description 10: Review the tagging technologies (like GPS, RFID) attached directly to animals for collecting spatio-temporal data, and the integration with wireless sensor networks.

Section 11: Integrating RFID Technology with Wireless Sensor Networks
Description 11: Explain how RFID technology is integrated with wireless sensor networks to enhance data collection and communication.

Section 12: Integrating GPS Technology and Wireless Sensor Networks
Description 12: Discuss the communication architectures for integrating GPS with wireless sensor networks, focusing on data transmission.

Section 13: Integration with Wireless Sensor Networks
Description 13: Describe the role of inertial sensors and radio communication in tracking and localizing animals using wireless sensor networks.

Section 14: Discussion
Description 14: Compare the technologies based on their data provision capabilities, performance metrics, and suitability for wildlife monitoring studies.

Section 15: Comparison of Technologies Based on Information They can Provide
Description 15: Provide a detailed comparison table of technologies regarding their ability to collect spatio-temporal features.

Section 16: Comparison of Technologies Based on Different Performance Metrics
Description 16: Compare the technologies in terms of disruptions, processing requirements, commercial availability, and invasiveness.

Section 17: Comparison of Technologies Based on the Subject of Study
Description 17: Compare the usage of different technologies across various wildlife species.

Section 18: Conclusions and Future Directions
Description 18: Summarize the current state of sensing technologies and propose future research directions in integrating wireless sensor networks for wildlife monitoring.