A Survey on Sensor Coverage and Visual Data Capturing/Processing/Transmission in Wireless Visual Sensor Networks
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paper_title: A Survey of Visual Sensor Networks

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Visual sensor networks have emerged as an important ::: class of sensor-based distributed intelligent systems, ::: with unique performance, complexity, and quality of service ::: challenges. Consisting of a large number of low-power camera nodes, ::: visual sensor networks support a great number of novel ::: vision-based applications. The camera nodes provide information ::: from a monitored site, performing distributed and collaborative ::: processing of their collected data. Using multiple cameras in the ::: network provides different views of the scene, which enhances ::: the reliability of the captured events. However, the large amount ::: of image data produced by the cameras combined with the ::: network's resource constraints require exploring new means ::: for data processing, communication, and sensor management. ::: Meeting these challenges of visual sensor networks requires ::: interdisciplinary approaches, utilizing vision processing, communications ::: and networking, and embedded processing. In this ::: paper, we provide an overview of the current state-of-the-art in ::: the field of visual sensor networks, by exploring several relevant ::: research directions. Our goal is to provide a better understanding ::: of current research problems in the different research fields of ::: visual sensor networks, and to show how these different research ::: fields should interact to solve the many challenges of visual sensor ::: networks.
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paper_title: Efficient visual sensor coverage algorithm in Wireless Visual Sensor Networks

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Traditional Wireless Sensor Networks (WSN) transmits the scalar data (e.g., temperature, irradiation) to the sink node. A new Wireless Visual Sensor Network (WVSN) that can transmit images is a more promising solution than the WSN on sensing, detecting and monitoring the environment to enhance awareness of the cyber, physical, and social contexts of our daily activities. Sensor coverage in WVSN is more challenging than in WSN due to besides the sensing range coverage, the Field of View (FoV) should also be considered in deploying the sensors. In this paper, we study the sensor coverage problem in WVSN. We first propose the mathematical model to formulate the sensor coverage problem in WVSN. We devise a heuristic algorithm (FoVIC) algorithm to tackle this sensor coverage problem in WVSN. The basic idea of FoVIC algorithm is to deploy a sensor one at a time that can cover the largest number of uncovered nodes and then the algorithm checks for any sensor deployed in the earlier stage that could be removed. From the computational experiments, they show that larger span angle could help the sensors to cover more nodes in bigger grid size and fewer sensors will be need in smaller grid size when in fixed sensing range and span angle.
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paper_title: Meerkats: A power-aware, self-managing wireless camera network for wide area monitoring

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We introduce Meerkats, a wireless network of batteryoperated camera nodes that can be used for monitoring and surveillance of wide areas. One distinguishing feature of Meerkats (when compared, for example, with systems like Cyclops [10]) is that our nodes are equipped with sufficient processing and storage capabilities to be able to run relatively sophisticated vision algorithms (e.g., motion estimation) locally and/or collaboratively. In previous work [9, 8, 7] we analyzed the energy consumption characteristics of the Meerkats nodes under different duty cycles, involving different power states of the system’s components. In this paper we present an analysis of the performance of the surveillance system as a function of the image acquisition rate and of the synchronization between cameras nodes. Our ultimate goal is to optimally balance the trade-off between application-specific performance requirements (e.g., event miss rate) and network lifetime (as a function of the energy consumption characteristics of each node).
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paper_title: Battery discharge characteristics of wireless sensors in building applications

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Sensor nodes in wireless networks often use batteries as their source of energy, but replacing or recharging exhausted batteries in a deployed network can be difficult and costly. Therefore, prolonging battery life becomes a principal objective in the design of wireless sensor networks (WSNs). There is little published data that quantitatively analyze a sensor node's lifetime under different operating conditions. This paper presents several experiments to quantify the impact of key wireless sensor network design and environmental parameters on battery performance. Our testbed consists of MicaZ motes, commercial alkaline batteries, and a suite of techniques for measuring battery performance. We evaluate known parameters, such as communication distance, working channel and operating power that play key roles in battery performance. Through extensive real battery discharge measurements, we expect our results to serve as a quantitative basis for future research in designing and implementing battery-efficient sensing applications and protocols.
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paper_title: Vision mesh: A novel video sensor networks platform for water conservancy engineering

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Video is an important medium for the observation of a variety of phenomena in the physical world such as for water conservancy engineering. Video sensor networks (VSN) consists of a large number of sensor nodes with cheap CMOS cameras, therefore, it has the ability of large scale visual monitoring. However, a kind of powerful and scalable platform is urgent for simulation and development of VSN. This paper proposed a novel and scalable video sensor networks platform named as Vision Mesh for water conservancy engineering. Vision Mesh is composed of a mass of image or video sensor nodes - Vision Motes, with which multi-view image or video information of FOV (Field of View) can be acquired simply. Vision Mote is built with Atmel ARM9 CPU and operated on Linux operating system, with TI CC2430 Zigbee module taken as wireless transceiver. Furthermore, OpenCV machine vision lib is migrated to Vision Mesh platform so as to improve video processing ability, therefore, Vision Mesh has the ability of image and video processing and is of strong scalability to extend performance. In this paper, we provide an overview of Vision Mesh architecture and provide an insightful platform for VSN.
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paper_title: Cyclops: in situ image sensing and interpretation in wireless sensor networks

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Despite their increasing sophistication, wireless sensor networks still do not exploit the most powerful of the human senses: vision. Indeed, vision provides humans with unmatched capabilities to distinguish objects and identify their importance. Our work seeks to provide sensor networks with similar capabilities by exploiting emerging, cheap, low-power and small form factor CMOS imaging technology. In fact, we can go beyond the stereo capabilities of human vision, and exploit the large scale of sensor networks to provide multiple, widely different perspectives of the physical phenomena.To this end, we have developed a small camera device called Cyclops that bridges the gap between the computationally constrained wireless sensor nodes such as Motes, and CMOS imagers which, while low power and inexpensive, are nevertheless designed to mate with resource-rich hosts. Cyclops enables development of new class of vision applications that span across wireless sensor network. We describe our hardware and software architecture, its temporal and power characteristics and present some representative applications.
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paper_title: Sensor networks for emergency response: challenges and opportunities

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Sensor networks, a new class of devices has the potential to revolutionize the capture, processing, and communication of critical data for use by first responders. CodeBlue integrates sensor nodes and other wireless devices into a disaster response setting and provides facilities for ad hoc network formation, resource naming and discovery, security, and in-network aggregation of sensor-produced data. We designed CodeBlue for rapidly changing, critical care environments. To test it, we developed two wireless vital sign monitors and a PDA-based triage application for first responders. Additionally, we developed MoteTrack, a robust radio frequency (RF)-based localization system, which lets rescuers determine their location within a building and track patients. Although much of our work on CodeBlue is preliminary, our initial experience with medical care sensor networks raised many exciting opportunities and challenges.
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paper_title: Battery Lifetime Prediction Model for a WSN Platform

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Wireless Sensor Network devices have by nature limited available energy to perform a wide range of demanding tasks. In order to maximize their operation lifetime, optimal resource management is an important challenge and its success requires methodical modeling of the factors contributing to the overall power consumption. Moreover, the power consumed is not always useful on its own, but it should rather express the expected lifetime concerning the device’s normal operation. To achieve such awareness, this paper contributes with a measuring methodology which involves combining power consumption of platform elementary functionalities with battery discharge characteristics, so that a practical, yet accurate battery lifetime prediction model can be formed.
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paper_title: MeshEye: a hybrid-resolution smart camera mote for applications in distributed intelligent surveillance

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INTRODUCTION Surveillance isoneofthepromising applications towhichsmart Distributed smartcameras havereceived increased focus inthe cameramotesforming a vision-enabled network canadd research community overthepastseveral months. Thenotion of increasing levels ofintelligence. We seeahighdegree ofin-node camerascombined withembeddedcomputation powerand processing incombination withdistributed reasoning algorithmsinterconnected through radio links opensupa newrealmof asthekeyenablers forsuchintelligent surveillance systems. To intelligent vision-enabled applications. Real-time image putthesesystems intopractice still requires a considerableprocessing anddistributed reasoning madepossible bysmart amountofresearch ranging frommotearchitectures, pixel- cameras cannotonlyenhance existing applications butalso processing algorithms, uptodistributed reasoning engines. This motivate newapplications. Potential application areas range from paperintroduces MeshEye, anenergy-efficient smartcamera homemonitoring, elderly care, andsmartenvironments to motearchitecture thathasbeendesigned withintelligent security andsurveillance inpublic orcorporate buildings. Critical surveillance asthetarget application inmind.Special attention is issues influencing thesuccess ofsmartcameradeployments for given toMeshEye's unique vision system: alow-resolution stereo suchapplications include reliable androbust operation withas vision system continuously determines position, range, andsize of little maintenance aspossible. movingobjects entering itsfield ofview.Thisinformation triggers acolor cameramodule toacquire ahigh-resolution image ncmpaisonito alar sensors, shsm r e pess sub-array cotinn th obet whic ca.eefiinlhumidity, velocity, andacceleration sensors, vision sensors pub-arocessedainysubseq staeIt offerredced complextly generate muchhigher bandwidth dataduetothetwo-dimensional processed insubsequent stages. Itoffers reduced complexity, naueothipxlary.Tesermutofawda response~~~~~~~~ tie.n oe osmto vrcnetoa nature oftheir pixel array. Thesheeramountofrawdata
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paper_title: A survey of visual sensor network platforms

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Recent developments in low-cost CMOS cameras have created the opportunity of bringing imaging capabilities to sensor networks. Various visual sensor platforms have been developed with the aim of integrating visual data to wireless sensor applications. The objective of this article is to survey current visual sensor platforms according to in-network processing and compression/coding techniques together with their targeted applications. Characteristics of these platforms such as level of integration, data processing hardware, energy dissipation, radios and operating systems are also explored and discussed.
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paper_title: Battery discharge characteristics of wireless sensor nodes: an experimental analysis

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Battery life extension is the principal driver for energy-efficient wireless sensor network (WSN) design. However, there is growing awareness that in order to truly maximize the operating life of battery-powered systems such as sensor nodes, it is important to discharge the battery in a manner that maximizes the amount of charge extracted from it. In spite of this, there is little published data that quantitatively analyzes the effectiveness with which modern wireless sensor nodes discharge their batteries, under different operating conditions. In this paper, we report on systematic experiments that we conducted to quantify the impact of key wireless sensor network design and environmental parameters on battery performance. Our testbed consists of MICA2DOT Motes, a commercial lithium- coin battery, and a suite of techniques for measuring battery per- formance. We evaluate the extent to which known electrochemical phenomena, such as rate-capacity characteristics, charge recov- ery and thermal effects, can play a role in governing the selection of key WSN design parameters such as power levels, packet sizes, etc. We demonstrate that battery characteristics significantly alter and complicate otherwise well-understood trade-offs in WSN design. In particular, we analyze the non-trivial implications of battery characteristics on WSN power control strategies, and find that a battery-aware approach to power level selection leads to a 52% increase in battery efficiency. We expect our results to serve as a quantitative basis for future research in designing battery-efficient sensing applications and protocols.
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paper_title: Maximizing Angle Coverage in Visual Sensor Networks

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In this paper, we study the angle coverage problem in visual sensor networks where all sensors are equipped with cameras. An object of interest moves around the network and the sensors near the object are responsible for capturing images of it. The angle coverage problem aims to identify a set of sensors that preserve all the angles of view of the object while fulfilling the image resolution requirement. The user is required to specify the minimum acceptable image resolution in the request. Only the images that fulfill the resolution requirement will be considered. In order to save transmission energy, the number of images to be sent should be minimized. We develop a distributed algorithm to identify the minimum set of sensors such that all these images cover the maximum angle of view of the target. Our simulation results show that our protocol can achieve significant reduction in transmission load while preserving the widest angle of view.
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paper_title: Deployment Optimization Strategy for a Two-Tier Wireless Visual Sensor Network

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Wireless visual sensor network (VSN) can be said to be a special class of wireless sensor network (WSN) with smart-cameras. Due to its visual sensing capability, it has become an effective tool for applications such as large area surveillance, environmental monitoring and objects tracking. Different from a conventional WSN, VSN typically includes relatively expensive camera sensors, enhanced flash memory and a powerful CPU. While energy consumption is dominated primarily by data transmission and reception, VSN consumes extra power onimage sensing, processing and storing operations. The well-known energy-hole problem of WSNs has a drastic impact on the lifetime of VSN, because of the additional energy consumption of a VSN. Most prior research on VSN energy issues are primarily focusedon a single device or a given specific scenario. In this paper, we propose a novel optimal two-tier deployment strategy for a large scale VSN. Our two-tier VSN architecture includes tier-1 sensing network with visual sensor nodes (VNs) and tier-2 network having only relay nodes (RNs). While sensing network mainly performs image data collection, relay network only for wards image data packets to the central sink node. We use uniform random distribution of VNs to minimize the cost of VSN and RNs are deployed following two dimensional Gaussian distribution so as to avoid energy-hole problem. Algorithms are also introduced that optimizes deployment parameters and are shown to enhance the lifetime of the VSN in a cost effective manner.
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paper_title: Eyes in the Sky: Decentralized Control for the Deployment of Robotic Camera Networks

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This paper presents a decentralized control strategy for positioning and orienting multiple robotic cameras to collectively monitor an environment. The cameras may have various degrees of mobility from six degrees of freedom, to one degree of freedom. The control strategy is proven to locally minimize a novel metric representing information loss over the environment. It can accommodate groups of cameras with heterogeneous degrees of mobility (e.g., some that only translate and some that only rotate), and is adaptive to robotic cameras being added or deleted from the group, and to changing environmental conditions. The robotic cameras share information for their controllers over a wireless network using a specially designed multihop networking algorithm. The control strategy is demonstrated in repeated experiments with three flying quadrotor robots indoors, and with five flying quadrotor robots outdoors. Simulation results for more complex scenarios are also presented.
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paper_title: Coverage estimation for crowded targets in visual sensor networks

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Coverage estimation is one of the fundamental problems in sensor networks. Coverage estimation in visual sensor networks (VSNs) is more challenging than in conventional 1-D (omnidirectional) scalar sensor networks (SSNs) because of the directional sensing nature of cameras and the existence of visual occlusion in crowded environments. This article represents a first attempt toward a closed-form solution for the visual coverage estimation problem in the presence of occlusions. We investigate a new target detection model, referred to as the certainty-based target detection (as compared to the traditional uncertainty-based target detection) to facilitate the formulation of the visual coverage problem. We then derive the closed-form solution for the estimation of the visual coverage probability based on this new target detection model that takes visual occlusions into account. According to the coverage estimation model, we further propose an estimate of the minimum sensor density that suffices to ensure a visual K-coverage in a crowded sensing field. Simulation is conducted which shows extreme consistency with results from theoretical formulation, especially when the boundary effect is considered. Thus, the closed-form solution for visual coverage estimation is effective when applied to real scenarios, such as efficient sensor deployment and optimal sleep scheduling.
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paper_title: Efficient visual sensor coverage algorithm in Wireless Visual Sensor Networks

paper_content:

Traditional Wireless Sensor Networks (WSN) transmits the scalar data (e.g., temperature, irradiation) to the sink node. A new Wireless Visual Sensor Network (WVSN) that can transmit images is a more promising solution than the WSN on sensing, detecting and monitoring the environment to enhance awareness of the cyber, physical, and social contexts of our daily activities. Sensor coverage in WVSN is more challenging than in WSN due to besides the sensing range coverage, the Field of View (FoV) should also be considered in deploying the sensors. In this paper, we study the sensor coverage problem in WVSN. We first propose the mathematical model to formulate the sensor coverage problem in WVSN. We devise a heuristic algorithm (FoVIC) algorithm to tackle this sensor coverage problem in WVSN. The basic idea of FoVIC algorithm is to deploy a sensor one at a time that can cover the largest number of uncovered nodes and then the algorithm checks for any sensor deployed in the earlier stage that could be removed. From the computational experiments, they show that larger span angle could help the sensors to cover more nodes in bigger grid size and fewer sensors will be need in smaller grid size when in fixed sensing range and span angle.
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paper_title: DISTRIBUTED COVERAGE GAMES FOR ENERGY-AWARE MOBILE SENSOR NETWORKS

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Inspired by current challenges in data-intensive and energy-limited sensor networks, we formulate a coverage optimization problem for mobile sensors as a (constrained) repeated multiplayer game. Each sensor tries to optimize its own coverage while minimizing the processing/energy cost. The sensors are subject to the informational restriction that the environmental distribution function is unknown a priori. We present two distributed learning algorithms where each sensor only remembers its own utility values and actions played during the last plays. These algorithms are proven to be convergent in probability to the set of (constrained) Nash equilibria and global optima of a certain coverage performance metric, respectively. Numerical examples are provided to verify the performance of our proposed algorithms.
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paper_title: Target detection and counting using a progressive certainty map in distributed visual sensor networks

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Visual sensor networks (VSNs) merge computer vision, image processing and wireless sensor network disciplines to solve problems in multi-camera applications by providing valuable information through distributed sensing and collaborative in-network processing. Collaboration in sensor networks is necessary not only to compensate for the processing, sensing, energy, and bandwidth limitations of each sensor node but also to improve the accuracy and robustness of the sensor network. Collaborative processing in VSNs is more challenging than in conventional scalar sensor networks (SSNs) because of two unique features of cameras, including the extremely higher data rate compared to that of scalar sensors and the directional sensing characteristics with limited field of view. In this paper, we study a challenging computer vision problem, target detection and counting in VSN environment. Traditionally, the problem is solved by counting the number of intersections of the backprojected 2D cones of each target. However, the existence of visual occlusion among targets would generate many false alarms. In this work, instead of resolving the uncertainty about target existence at the intersections, we identify and study the non-occupied areas in the cone and generate the so-called certainty map of non-existence of targets. This way, after fusing inputs from a set of sensor nodes, the unresolved regions on the certainty map would be the location of target. This paper focuses on the design of a light-weight, energy-efficient, and robust solution where not only each camera node transmits a very limited amount of data but that a limited number of camera nodes is used. We propose a dynamic itinerary for certainty map integration where the entire map is progressively clarified from sensor to sensor. When the confidence of the certainty map is satisfied, a geometric counting algorithm is applied to find the estimated number of targets. In the conducted experiments using real data, the results of the proposed distributed and progressive method shows effectiveness in detection accuracy and energy and bandwidth efficiency.
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paper_title: Distributed target localization using a progressive certainty map in visual sensor networks

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Collaboration in visual sensor networks (VSNs) is essential not only to compensate for the processing, sensing, energy, and bandwidth limitations of each sensor node but also to improve the accuracy and robustness of the network. In this paper, we study target localization in VSNs, a challenging computer vision problem because of two unique features of cameras, including the extremely higher data rate and the directional sensing characteristics with limited field of view. Traditionally, the problem is solved by localizing the targets at the intersections of the back-projected 2D cones of each target. However, the existence of visual occlusion among targets would generate many false alarms. In this work, instead of resolving the uncertainty about target existence at the intersections, we identify and study the non-occupied areas in the cone and generate the so-called certainty map of non-existence of targets. As a result, after fusing inputs from a set of sensor nodes, the unresolved regions on the certainty map would be the location of targets. This paper focuses on the design of a light-weight, energy-efficient, and robust solution where not only each camera node transmits a very limited amount of data but that a limited number of camera nodes is involved. We propose a dynamic itinerary for certainty map integration where the entire map is progressively clarified from sensor to sensor. When the confidence of the certainty map is satisfied, targets are localized at the remaining unresolved regions in the certainty map. Based on results obtained from both simulation and real experiments, the proposed progressive method shows effectiveness in detection accuracy as well as energy and bandwidth efficiency.
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paper_title: Determining vision graphs for distributed camera networks using feature digests

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We propose a decentralized method for obtaining the vision graph for a distributed, ad-hoc camera network, in which each edge of the graph represents two cameras that image a sufficiently large part of the same environment. Each camera encodes a spatially well-distributed set of distinctive, approximately viewpoint-invariant feature points into a fixed-length "feature digest" that is broadcast throughout the network. Each receiver camera robustly matches its own features with the decompressed digest and decides whether sufficient evidence exists to form a vision graph edge. We also show how a camera calibration algorithm that passes messages only along vision graph edges can recover accurate 3D structure and camera positions in a distributed manner. We analyze the performance of different message formation schemes, and show that high detection rates (>0.8) can be achieved while maintaining low false alarm rates (<0.05) using a simulated 60-node outdoor camera network.
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paper_title: A Spatial Correlation-Based Image Compression Framework for Wireless Multimedia Sensor Networks

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Data redundancy caused by correlation has motivated the application of collaborative multimedia in-network processing for data filtering and compression in wireless multimedia sensor networks (WMSNs). This paper proposes an information theoretic image compression framework with an objective to maximize the overall compression of the visual information gathered in a WMSN. The novelty of this framework relies on its independence of specific image types and coding algorithms, thereby providing a generic mechanism for image compression under different coding solutions. The proposed framework consists of two components. First, an entropy-based divergence measure (EDM) scheme is proposed to predict the compression efficiency of performing joint coding on the images collected by spatially correlated cameras. The EDM only takes camera settings as inputs without requiring statistics of real images. Utilizing the predicted results from EDM, a distributed multi-cluster coding protocol (DMCP) is then proposed to construct a compression-oriented coding hierarchy. The DMCP aims to partition the entire network into a set of coding clusters such that the global coding gain is maximized. Moreover, in order to enhance decoding reliability at data sink, the DMCP also guarantees that each sensor camera is covered by at least two different coding clusters. Experiments on H.264 standards show that the proposed EDM can effectively predict the joint coding efficiency from multiple sources. Further simulations demonstrate that the proposed compression framework can reduce 10%-23% total coding rate compared with the individual coding scheme, i.e., each camera sensor compresses its own image independently.
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paper_title: Distributed metric calibration of ad hoc camera networks

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We discuss how to automatically obtain the metric calibration of an ad hoc network of cameras with no centralized processor. We model the set of uncalibrated cameras as nodes in a communication network, and propose a distributed algorithm in which each camera performs a local, robust bundle adjustment over the camera parameters and scene points of its neighbors in an overlay “vision graph.” We analyze the performance of the algorithm on both simulated and real data, and show that the distributed algorithm results in a fairer allocation of messages per node while achieving comparable calibration accuracy to centralized bundle adjustment.
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paper_title: A Camera Nodes Correlation Model Based on 3D Sensing in Wireless Multimedia Sensor Networks

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In wireless multimedia sensor networks, multiple camera sensor nodes generally are used for gaining enhanced observations of a certain area of interest. This brings on the visual information retrieved from adjacent camera nodes usually exhibits high levels of correlation. In this paper, first, based on the analysis of 3D directional sensing model of camera sensor nodes, a correlation model is proposed by measuring the intersection area of multiple camera nodes’ field of views. In this model, there is a asymmetrical relationship of the correlation between two camera nodes. Then, to farthest eliminate the data redundancy and use the node collaboration characteristic of wireless (multimedia) sensor networks, two kinds of cluster structure, camera sensor nodes cluster, and common sensor nodes cluster are established to cooperate on image processing and transmission tasks. A set of experiments are performed to investigate the proposed correlation coefficient. Further simulations based on a sample of monitoring a crossing by three correlative camera nodes show that the proposed network topology and image fusion and transmission scheme released the pressure of camera node greatly and reduce the network energy consumption of communication of the whole network efficiently.
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paper_title: Distributed collaborative camera actuation for redundant data elimination in wireless multimedia sensor networks

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Given the high cost of processing and communicating the multimedia data in wireless multimedia sensor networks (WMSNs), it is important to reduce possible data redundancy. Therefore, camera sensors should only be actuated when an event is detected within their vicinity. In the meantime, the coverage of the event should not be compromised. In this paper, we propose a low-cost distributed actuation scheme which strives to turn on the least number of cameras to avoid possible redundancy in the multimedia data while still providing the necessary event coverage. The basic idea of this scheme is the collaboration of camera sensors that have heard from scalar sensors about an occurring event to minimize the possible coverage overlaps. This is done by either counting the number of scalar sensors or determining the event boundaries with scalar sensors. Through simulation, we show how the distributed scheme performs in terms of coverage under several centralized and random deployment schemes. We also compare the performance with the case when all the cameras in the vicinity are actuated and when blockages in the region exist.
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paper_title: A Spatial Correlation Model for Visual Information in Wireless Multimedia Sensor Networks

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Wireless multimedia sensor networks (WMSNs) are interconnected devices that allow retrieving video and audio streams, still images, and scalar data from the environment. In a densely deployed WMSN, there exists correlation among the visual information observed by cameras with overlapped field of views. This paper proposes a novel spatial correlation model for visual information in WMSNs. By studying the sensing model and deployments of cameras, a spatial correlation function is derived to describe the correlation characteristics of visual information observed by cameras with overlapped field of views. The joint effect of multiple correlated cameras is also studied. An entropy-based analytical framework is developed to measure the amount of visual information provided by multiple cameras in the network. Furthermore, according to the proposed correlation function and entropy-based framework, a correlation-based camera selection algorithm is designed. Experimental results show that the proposed spatial correlation function can model the correlation characteristics of visual information in WMSNs through low computation and communication costs. Further simulations show that, given a distortion bound at the sink, the correlation-based camera selection algorithm requires fewer cameras to report to the sink than the random selection algorithm.
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paper_title: Vision Graph Construction in Wireless Multimedia Sensor Networks

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In Wireless multimedia sensor networks (WMSNs), two graphs, communication network graph and vision graph, can be established. The camera nodes connected in the vision graph share overlapped field of views (FOVs) and they depend on the densely deployed relay nodes in the communication network graph to communicate with each other. Given a uniformly deployed camera sensor network with relay nodes, the problem is to find the number of hops for the vision-graph- neighbor-searching messages to construct the vision graph in an energy efficient way. In this paper, mathematical models are developed to analyze the FOV overlap of the camera nodes and the multi-hop communications in two dimensional topologies, which are utilized to analyze the optimal hop number. In addition, simulations are conducted to verify our models.
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paper_title: Virtual View Image over Wireless Visual Sensor Network

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In general, visual sensors are applied to build virtual view images. When number of visual sensors increases then quantity and quality of the information improves. However, the view images generation is a challenging task in Wireless Visual Sensor Network environment due to energy restriction, computation complexity, and bandwidth limitation. Hence this paper presents a new method of virtual view images generation from selected cameras on Wireless Visual Sensor Network. The aim of the paper is to meet bandwidth and energy limitations without reducing information quality. The experiment results showed that this method could minimize number of transmitted imageries with sufficient information..
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paper_title: FoV-Clustering as a solution to a novel camera node activation problem in WVSNs

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In Wireless Visual Sensor Networks (WVSNs), node selection and organization to realize applications is the title of some research fields known as network topology models that can be classified into two main categories of single-tier and multi-tier. According to the literature, only multi-tier topology model is able to provide a balance between WVSNs objectives such as low cost, maximum coverage, minimum energy consumption, high functionality, and good reliability. In a general architecture for this model, the lowest tier consists of scalar nodes that can activate camera nodes of upper tier only if necessary. However, regarding the inter-tier communication radio range and camera nodes' covered area, in many cases the activated cameras do not detect any objects. The mentioned problem which wastes energy and processor time for doing unneeded image capturing and object detection operations is introduced for the first time in this paper. Besides, a new clustering method with the aim of determining the scalar nodes located inside the area covered by a camera node is proposed as a solution. As the simulation results indicate, this solution has succeeded in saving camera nodes' energy and prolonging network lifetime.
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paper_title: MAC-Aware and Power-Aware Image Aggregation Scheme in Wireless Visual Sensor Networks

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Traditional wireless sensor networks (WSNs) transmit the scalar data (e.g., temperature and irradiation) to the sink node. A new wireless visual sensor network (WVSN) that can transmit images data is a more promising solution than the WSN on sensing, detecting, and monitoring the environment to enhance awareness of the cyber, physical, and social contexts of our daily activities. However, the size of image data is much bigger than the scalar data that makes image transmission a challenging issue in battery-limited WVSN. In this paper, we study the energy efficient image aggregation scheme in WVSN. Image aggregation is a possible way to eliminate the redundant portions of the image captured by different data source nodes. Hence, transmission power could be reduced via the image aggregation scheme. However, image aggregation requires image processing that incurs node processing power. Besides the additional energy consumption from node processing, there is another MAC-aware retransmission energy loss from image aggregation. In this paper, we first propose the mathematical model to capture these three factors (image transmission, image processing, and MAC retransmission) in WVSN. Numerical results based on the mathematical model and real WVSN sensor node (i.e., Meerkats node) are performed to optimize the energy consumption tradeoff between image transmission, image processing, and MAC retransmission.
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paper_title: Modeling and assessing quality of information in multisensor multimedia monitoring systems

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Current sensor-based monitoring systems use multiple sensors in order to identify high-level information based on the events that take place in the monitored environment. This information is obtained through low-level processing of sensory media streams, which are usually noisy and imprecise, leading to many undesired consequences such as false alarms, service interruptions, and often violation of privacy. Therefore, we need a mechanism to compute the quality of sensor-driven information that would help a user or a system in making an informed decision and improve the automated monitoring process. In this article, we propose a model to characterize such quality of information in a multisensor multimedia monitoring system in terms of certainty, accuracy/confidence and timeliness. Our model adopts a multimodal fusion approach to obtain the target information and dynamically compute these attributes based on the observations of the participating sensors. We consider the environment context, the agreement/disagreement among the sensors, and their prior confidence in the fusion process in determining the information of interest. The proposed method is demonstrated by developing and deploying a real-time monitoring system in a simulated smart environment. The effectiveness and suitability of the method has been demonstrated by dynamically assessing the value of the three quality attributes with respect to the detection and identification of human presence in the environment.
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paper_title: A Spatial Correlation-Based Image Compression Framework for Wireless Multimedia Sensor Networks

paper_content:

Data redundancy caused by correlation has motivated the application of collaborative multimedia in-network processing for data filtering and compression in wireless multimedia sensor networks (WMSNs). This paper proposes an information theoretic image compression framework with an objective to maximize the overall compression of the visual information gathered in a WMSN. The novelty of this framework relies on its independence of specific image types and coding algorithms, thereby providing a generic mechanism for image compression under different coding solutions. The proposed framework consists of two components. First, an entropy-based divergence measure (EDM) scheme is proposed to predict the compression efficiency of performing joint coding on the images collected by spatially correlated cameras. The EDM only takes camera settings as inputs without requiring statistics of real images. Utilizing the predicted results from EDM, a distributed multi-cluster coding protocol (DMCP) is then proposed to construct a compression-oriented coding hierarchy. The DMCP aims to partition the entire network into a set of coding clusters such that the global coding gain is maximized. Moreover, in order to enhance decoding reliability at data sink, the DMCP also guarantees that each sensor camera is covered by at least two different coding clusters. Experiments on H.264 standards show that the proposed EDM can effectively predict the joint coding efficiency from multiple sources. Further simulations demonstrate that the proposed compression framework can reduce 10%-23% total coding rate compared with the individual coding scheme, i.e., each camera sensor compresses its own image independently.
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paper_title: Multimodal fusion for multimedia analysis: a survey

paper_content:

This survey aims at providing multimedia researchers with a state-of-the-art overview of fusion strategies, which are used for combining multiple modalities in order to accomplish various multimedia analysis tasks. The existing literature on multimodal fusion research is presented through several classifications based on the fusion methodology and the level of fusion (feature, decision, and hybrid). The fusion methods are described from the perspective of the basic concept, advantages, weaknesses, and their usage in various analysis tasks as reported in the literature. Moreover, several distinctive issues that influence a multimodal fusion process such as, the use of correlation and independence, confidence level, contextual information, synchronization between different modalities, and the optimal modality selection are also highlighted. Finally, we present the open issues for further research in the area of multimodal fusion.
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paper_title: On the adoption of multiview video coding in wireless multimedia sensor networks

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This article explores the potential performance gains achievable by applying the multiview video coding paradigm in wireless multimedia sensor networks (WMSN). Recent studies have illustrated how significant performance gains (in terms of energy savings and consequently of network lifetime) can be obtained by leveraging the spatial correlation among partially overlapped fields of view of multiple video cameras observing the same scene. A crucial challenge is then how to describe the correlation among different views of the same scene with accurate yet simple metrics. In this article, we first experimentally assess the performance gains of multiview video coding as a function of metrics capturing the correlation among different views. We compare their effectiveness in predicting the correlation among different views and consequently assess the potential performance gains of multiview video coding in WMSNs. In particular, we show that, in addition to geometric information, occlusions and movement need to be considered to fully take advantage of multiview video coding.
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paper_title: Distributed Algorithms for Network Lifetime Maximization in Wireless Visual Sensor Networks

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Network lifetime maximization is a critical issue in wireless sensor networks since each sensor has a limited energy supply. In contrast with conventional sensor networks, video sensor nodes compress the video before transmission. The encoding process demands a high power consumption, and thus raises a great challenge to the maintenance of a long network lifetime. In this paper, we examine a strategy for maximizing the network lifetime in wireless visual sensor networks by jointly optimizing the source rates, the encoding powers, and the routing scheme. Fully distributed algorithms are developed using the Lagrangian duality to solve the lifetime maximization problem. We also examine the relationship between the collected video quality and the maximal network lifetime. Through extensive numerical simulations, we demonstrate that the proposed algorithm can achieve a much longer network lifetime compared to the scheme optimized for the conventional wireless sensor networks.
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paper_title: Ant-based routing for wireless multimedia sensor networks using multiple QoS metrics

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In wireless sensor networks, most routing protocols consider energy savings as the main objective and assume data traffic with unconstrained delivery requirements to be a given. However, the introduction of video and imaging sensors unveils additional challenges. The transmission of video and imaging data requires both energy efficiency and QoS assurance (end-to-end delay and packet loss requirements), in order to ensure the efficient use of sensor resources as well as the integrity of the information collected. This paper presents a QoS routing model for Wireless Multimedia Sensor Networks (WMSN). Moreover, based on the traditional ant-based algorithm, an ant-based multi-QoS routing metric (AntSensNet) is proposed. The AntSensNet protocol builds a hierarchical structure on the network before choosing suitable paths to meet various QoS requirements from different kinds of traffic, thus maximizing network utilization, while improving its performance. In addition, AntSensNet is able to use a efficient multi-path video packet scheduling in order to get minimum video distortion transmission. Finally, extensive simulations are conducted to assess the effectiveness of this novel solution and a detailed discussion regarding the effects of different system parameters is provided. Compared to typical routing algorithms in sensor networks and the traditional ant-based algorithm, this new algorithm has better convergence and provides significantly better QoS for multiple types of services in wireless multimedia sensor networks.
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paper_title: Correlation-Aware QoS Routing With Differential Coding for Wireless Video Sensor Networks

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The spatial correlation of visual information retrieved from distributed camera sensors leads to considerable data redundancy in wireless video sensor networks, resulting in significant performance degradation in energy efficiency and quality-of-service (QoS) satisfaction. In this paper, a correlation-aware QoS routing algorithm (CAQR) is proposed to efficiently deliver visual information under QoS constraints by exploiting the correlation of visual information observed by different camera sensors. First, a correlation-aware inter-node differential coding scheme is designed to reduce the amount of traffic in the network. Then, a correlation-aware load balancing scheme is proposed to prevent network congestion by splitting the correlated flows that cannot be reduced to different paths. Finally, the correlation-aware schemes are integrated into an optimization QoS routing framework with an objective to minimize energy consumption subject to delay and reliability constraints. Simulation results demonstrate that the proposed routing algorithm achieves efficient delivery of visual information under QoS constraints in wireless video sensor networks.
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paper_title: Linear network coding

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Consider a communication network in which certain source nodes multicast information to other nodes on the network in the multihop fashion where every node can pass on any of its received data to others. We are interested in how fast each node can receive the complete information, or equivalently, what the information rate arriving at each node is. Allowing a node to encode its received data before passing it on, the question involves optimization of the multicast mechanisms at the nodes. Among the simplest coding schemes is linear coding, which regards a block of data as a vector over a certain base field and allows a node to apply a linear transformation to a vector before passing it on. We formulate this multicast problem and prove that linear coding suffices to achieve the optimum, which is the max-flow from the source to each receiving node.
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paper_title: Event-driven geographic routing for wireless image sensor networks

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We propose a distributed routing scheme with adjustable priority support for event-driven wireless sensor networks. The network nodes are assumed to generate periodic data packets that are reported to the destination via multihop routing. Nodes may also infrequently detect an event from which a large number of packets are produced and need to be reported. These high-bandwidth event reports may cause packet queues to develop at the routing nodes along paths to the destination. The proposed routing scheme employs a cost function based on the location information as well as the current queue lengths and remaining energies at the neighboring nodes as a basis for next hop selection. Our scheme also implements a set of relative priority levels for the event-based and periodic data packets. Simulation results are presented and indicate improved network lifetime, lower end-to-end average and maximum delays, and significantly reduced buffer size requirements for the network nodes. the periodic measurements. Handling large bursts of event packets can cause significant local delays along the best path chosen by existing geographic routing schemes. The proposed distributed routing scheme associates a cost to each hop that depends on its existing queue. The remaining energy at the node is also considered as a cost parameter. Cost functions defined for queue size and energy are added to the position-based cost for greedy routing towards the destination. Providing quality of service (QoS) support on an end-to- end basis is infeasible in wireless sensor networks designed to operate under distributed decision making mechanisms. Our work aims to improve end-to-end latency and provide best- effort QoS support in geographic routing by employing two mechanisms in its distributed routing scheme: a cost function based on the queue length at the routing candidates, and a set of relative priority levels for the different packet types. The effect of these priorities is incorporated into the queue length cost function of the receiving node and is used by the transmitting node to order the transmission of packets between the two types. As our routing scheme is based on using local information, the notion of an end-to-end QoS guarantee does not apply. However, as we explain later, such guarantees may not apply to event-driven routing in wireless sensor networks due to the multiplicity of participating source nodes reporting an event, and the reliance of most designs on the incorporation of fault tolerance and multi-path routing schemes in the design of these networks. Performance of the proposed routing scheme is studied via simulation. The effect of different weighting factors for the three routing cost function components on the network perfor- mance is analyzed. In particular, using queue cost significantly lowers the average and maximum delays, and drastically re- duces the node buffer size requirements. Furthermore, includ- ing energy cost significantly increases the network lifetime. More generally, we see that adding the queue size and energy costs to the cost function of greedy routing and incorporating a packet type prioritization scheme allows various tradeoffs to be made between the different performance factors of the network. While MAC layer prioritization schemes may also provide QoS support, they are not the focus of this paper. We assume a periodic MAC scheme in our simulations. The remainder of the paper is organized as follows. In Section II an overview of our proposed routing scheme is
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paper_title: A routing mechanism based on the sensing relevancies of source nodes for time-critical applications in visual sensor networks

paper_content:

Wireless sensor networks may be deployed to retrieve visual information from the monitored field, enriching monitoring and control applications. Whenever a set of camera-enabled sensor nodes are deployed for time-critical monitoring, visual information as still images and video streams may need to reach the sink as soon as possible, requiring a differentiated treating of the network when compared with non-critical visual data. In such way, considering that source nodes may have different sensing relevancies for the application, according to the desired monitoring tasks and the current sensors' poses and fields of view, we propose a delay-aware multihop routing mechanism where higher relevant visual data packets are routed through paths with lower end-to-end delay. As sensor nodes are expected to be energy-constrained, transmitting only high-relevant packets through shorter/faster paths may prolong their lifetime and assure longer time-critical delivering, with low impact to the overall monitoring quality.
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paper_title: On ant routing algorithms in ad hoc networks with critical connectivity

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This paper shows a novel self-organizing approach for routing datagrams in ad hoc networks, called Distributed Ant Routing (DAR). This approach belongs to the class of routing algorithms inspired by the behavior of the ant colonies in locating and storing food. The effectiveness of the heuristic algorithm is supported by mathematical proofs and demonstrated by a comparison with the well-known Ad hoc On Demand Distance Vector (AODV) algorithm. The differences and the similarities of the two algorithms have been highlighted. Results obtained by a theoretical analysis and a simulation campaign show that DAR allows obtaining some important advantages that makes it a valuable candidate to operate in ad hoc networks and the same method helps in the selection of the algorithm parameters. Since the approach aims at minimizing complexity in the nodes at the expenses of the optimality of the solution, it results to be particularly suitable in environments where fast communication establishment and minimum signalling overhead are requested. These requirements are typical of ad hoc networks with critical connectivity, as described in the paper. Thus the performance of the proposed algorithm are shown in ad hoc networks with critical connectivity and compared to some existing ad hoc routing algorithms.
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paper_title: Joint Coding/Routing Optimization for Distributed Video Sources in Wireless Visual Sensor Networks

paper_content:

This paper studies a joint coding/routing optimization between network lifetime and video distortion by applying information theory to wireless visual sensor networks for correlated sources. Arbitrary coding [distributed video coding and network coding (NC)] from both combinatorial optimization and information theory could make significant progress toward the performance limit and tractable. Also, multipath routing can spread energy utilization across nodes within the entire network to keep a potentially longer lifetime, and solve the wireless contention issues by the splitting traffic. The objective function not only keeps the total energy consumption of encoding power, transmission power, and reception power minimized, but ensures the information received by sink nodes to approximately reconstruct the visual field. Also, a generalized power consumption model for distributed video sources is developed, in which the coding complexity of Key frames and Wyner-Ziv frames is measured by translating specific coding behavior into energy consumption. On the basis of the distributed multiview video coding and NC-based multipath routing, the balance problem between lifetime (costs) and distortion (capacity) is modeled as an optimization formulation with a fully distributed solution. Through a primal decomposition, a two-level optimization is relaxed with Lagrangian dualization and solved by the gradient algorithm. The low-level optimization problem is further decomposed into a secondary master dual problem with four cross-layer subproblems: a rate control problem, a channel contention problem, a distortion control problem, and an energy conservation problem. The implementation of the distributed algorithm is discussed with regard to the communication overhead and dynamic network change. Simulation results validate the convergence and performance of the proposed algorithm.
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paper_title: Joint Coding/Routing Optimization for Correlated Sources in Wireless Visual Sensor Networks

paper_content:

This paper studies a joint coding/routing optimization between network lifetime and rate-distortion, by applying information theory to wireless visual sensor networks for correlated sources. Arbitrary coding (distributed source coding and network coding) from both combinatorial optimization and information theory could make significant progress towards the performance limit of information networks and tractable. Also, multipath routing can spread energy utilization across nodes within the entire network to keep a potentially longer lifetime, and solve the wireless contention issues by the splitting traffic. The objective function not only keeps a total energy consumption of encoding power, transmission power, and reception power minimized, but ensures the information received by sink nodes to approximately reconstruct the visual field. Based on the localized Slepian-Wolf coding and network coding-based multipath routing, the balance problem between distortion (capacity) and lifetime (costs) is modeled as an optimization formulation with a distributed solution. Through a primal decomposition, a two-level optimization is relaxed with Lagrangian dualization and solved with the gradient algorithm. The low-level optimization problem is decomposed into a secondary master dual problem (encoding, energy, and congestion prices update) with four cross-layer subproblems: a rate control problem, a channel contention problem, a distortion control problem, and an energy conservation problem. Numerical results validate the convergence and performance of the proposed algorithm.
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paper_title: Data relevance dynamic routing protocol for Wireless Visual Sensor Networks

paper_content:

Survivability is crucial in Wireless Visual Sensor Networks (WVSNs) especially when they are used for monitoring and tracking applications with limited available resources. In this paper we are proposing the use of a data relevance dynamic routing protocol that tries to keep a balance between the energy consumption and the packet delay in a WVSN. The proposed dynamic routing protocol follows opportunistic routing approaches. The next node selection criterion can change the routing path dynamically following the network conditions and the channel availability while the energy consumption per node is also considered. Simulation results are presented that show an increase in network lifetime of up to 30% compared with traditional routing while the overall packet delay remains similar.
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paper_title: Distributed Adaptive Sampling, Forwarding, and Routing Algorithms for Wireless Visual Sensor Networks

paper_content:

The efficient management of the limited energy resources of a wireless visual sensor network is central to its successful operation. Within this context, this paper focuses on the adaptive sampling, forwarding, and routing actions of each node in order to maximise the information value of the data collected. These actions are inter-related in this setting because each node's energy consumption must be optimally allocated between sampling and transmitting its own data, receiving and forwarding the data of other nodes, and routing any data. Thus, we develop two optimal decentralised algorithms to solve this distributed constraint optimization problem. The first assumes that the route by which data is forwarded to the base station is fixed, and then calculates the optimal sampling, transmitting, and forwarding actions that each node should perform. The second assumes flexible routing, and makes optimal decisions regarding both the integration of actions that each node should choose, and also the route by which the data should be forwarded to the base station. The two algorithms represent a trade-off in optimality, communication cost, and processing time. In an empirical evaluation on sensor networks (whose underlying communication networks exhibit loops), we show that the algorithm with flexible routing is able to deliver approximately twice the quantity of information to the base station compared to the algorithm using fixed routing (where an arbitrary choice of route is made). However, this gain comes at a considerable communication and computational cost (increasing both by a factor of 100 times). Thus, while the algorithm with flexible routing is suitable for networks with a small numbers of nodes, it scales poorly, and as the size of the network increases, the algorithm with fixed routing is favoured.
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paper_title: Ant Based Routing Protocol for Visual Sensors

paper_content:

In routing protocols, sensor nodes tend to route events (images) captured to a particular destination (sink) using the most efficient path. The power and bandwidth required to transmit video data from hundreds of cameras to a central location for processing at a high success rate would be enormous. In this work, captured packets were routed from different sensors placed at different locations to the sink using the best path. Since the captured images (packets) need to be routed to the destination (sink) at regular interval and within a predefined period of time, while consuming low energy without performance degradation, Ant based routing which utilizes the behavior of real ants searching for food through pheromone deposition, while dealing with problems that need to find paths to goals, through the simulating behavior of ant colony is adopted. In this end, we present an Improved Energy-Efficient Ant- Based Routing (IEEABR) Algorithm in Visual Sensor Networks. Compared to the state-of-the-art Ant-Based routing protocols; Basic Ant-Based Routing (BABR) Algorithm, Sensor-driven and Cost-aware ant routing (SC), Flooded Forward ant routing (FF), Flooded Piggybacked ant routing (FP), and Energy- Efficient Ant-Based Routing (EEABR), the proposed IEEABR approach have advantages of reduced energy usage, delivering events packets at high success rate with low latency, increases the network lifetime, and actively performing its set target without performance degradation. The performance evaluations for the algorithms on a real application are conducted in a well known WSNs MATLAB-based simulator (RMASE) using both static and dynamic scenario.
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paper_title: SIoT: Giving a Social Structure to the Internet of Things

paper_content:

The actual development of the Internet of Things (IoT) needs major issues related to things' service discovery and composition to be addressed. This paper proposes a possible approach to solve such issues. We introduce a novel paradigm of "social network of intelligent objects", namely the Social Internet of Things (SIoT), based on the notion of social relationships among objects. Following the definition of a possible social structure among objects, a preliminary architecture for the implementation of SIoT is presented. Through the SIoT paradigm, the capability of humans and devices to discover, select, and use objects with their services in the IoT is augmented. Besides, a level of trustworthiness is enabled to steer the interaction among the billions of objects which will crowd the future IoT.
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paper_title: The Social Internet of Things (SIoT) - When social networks meet the Internet of Things: Concept, architecture and network characterization

paper_content:

Recently there has been quite a number of independent research activities that investigated the potentialities of integrating social networking concepts into Internet of Things (IoT) solutions. The resulting paradigm, named Social Internet of Things (SIoT), has the potential to support novel applications and networking services for the IoT in more effective and efficient ways. In this context, the main contributions of this paper are the following: (i) we identify appropriate policies for the establishment and the management of social relationships between objects in such a way that the resulting social network is navigable; (ii) we describe a possible architecture for the IoT that includes the functionalities required to integrate things into a social network; (iii) we analyze the characteristics of the SIoT network structure by means of simulations.
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Title: A Survey on Sensor Coverage and Visual Data Capturing/Processing/Transmission in Wireless Visual Sensor Networks

Section 1: Introduction
Description 1: This section introduces the concept of Wireless Visual Sensor Networks (WVSNs), their unique characteristics compared to traditional Wireless Sensor Networks (WSNs), and the main research challenges and opportunities in sensor coverage and visual data handling.

Section 2: Node Hardware Components in WVSNs
Description 2: This section reviews the five major hardware components of visual sensor nodes, discusses the tradeoffs involved, and summarizes the node components for existing WVSN platforms.

Section 3: Sensor Coverage/Deployment in WVSNs
Description 3: This section discusses the sensor coverage problem in WVSNs, including the additional considerations for view angle coverage and occlusion, and reviews existing research on sensor deployment strategies in WVSNs.

Section 4: Visual Data Capture in WVSNs
Description 4: This section studies existing works on visual data capture, including methods to identify the minimum set of sensors needed to cover an object and techniques to handle redundant or supportive image data from overlapping Fields of View (FoVs).

Section 5: Visual Data Processing in WVSNs
Description 5: This section examines existing visual data processing techniques, including image/video aggregation, quality measurement, and collaborative data processing among camera sensors, and discusses challenges due to limited hardware resources.

Section 6: Visual Data Transmission in WVSNs
Description 6: This section surveys existing works on visual data transmission schemes in WVSNs, focusing on routing protocols, network coding, and strategies to balance between energy consumption, bandwidth, and data quality.

Section 7: Social Networking Paradigms in WVSNs
Description 7: This section explores the application of social networking concepts to WVSNs, discussing how cooperation among sensor nodes can be managed using social behavior models and presents the Social Internet of Things (SIoT) as a potential research direction.

Section 8: Conclusions
Description 8: This section concludes the survey by summarizing the unique challenges presented by WVSNs, reviewing the main research findings, and highlighting open issues that still need to be addressed in sensor coverage and visual data handling.