A Survey on Pollution Monitoring Using Sensor Networks in Environment Protection
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paper_title: Development of a new sensor for total organic carbon (TOC) determination

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A sensor to determine TOC is described. It is based on the photoassisted degradation of organic compounds concurring to TOC and on the determination of the resultant CO2. The sensor was successfully tested on target molecules, demonstrating that the linear correlation constant between TOC values and produced CO2 varies according to the considered compound so that absolute value determination is not possible in largely heterogeneous solutions but can only be referred to reference compounds on the TOC scale.
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paper_title: Highly sensitive ozone sensor

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Abstract A highly sensitive and reliable O 3 gas sensor (below 100 ppb) has been studied using an In 2 O 3 semiconductor thin film. The effects of various metal-oxide catalysts added to the film surface have been examined. The additives greatly affect the sensitivity characteristics of the O 3 gas sensor, especially the temperature dependence of O 3 sensitivity. The peak of the temperature-dependence curve for the Fe-oxide-added film is located at about 370 °C, but the peak for the Cs-oxide (or Rb-oxide)-added film is shifted up to about 500 °C. The peaks for other metal-oxide additives (Ba, Mg, Ni, Ce, Cr and Zr) are located between 400 and 460 °C. The peak for Mo-oxide (or W-oxide) is also shifted up to above 465 °C. The location of the peaks of the temperature-dependence curves is likely to relate to their standard enthalpies of formation (° H ° f ) of the hydroxides (or the oxyacids) from their oxides. The above phenomena suggest the effects of the surface hydroxyl groups on the O 3 sensitivity. It is found that the Fe-oxide-added In 2 O 3 semiconductor thin film has a high sensitivity and reliability to low concentrations of O 3 below 100 ppb. The sensor is able to detect 8 ppb O 3 with sufficient response. It also exhibits a power-law behaviour to O 3 concentration between 8 ppb and 10 ppm, R out α C 0.38 . It may be capable of detecting low concentrations of O 3 down to 1 ppb. Thus, the present sensor has sufficiently high sensitivity and reliability to observe low concentrations of natural O 3 in the atmosphere.
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paper_title: Smart-sensor approach for a fibre-optic-based residual chlorine monitor

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Developments of an optical-fibre-based sensor system for monitoring residual chlorine in water are discussed. The system, based on differential absorption spectroscopy, utilizes a novel miniature monolithic diode array spectrometer operating in the ultraviolet and visible (UV-Vis) region of the spectrum in combination with an optical flow-through cell of length 430 mm and a computer-controlled deuterium lamp source. The sensor, having a detection limit of 0.2 mg l−1 of free chlorine in water, relies on the fact that the OCl− ion, in which form dissolved chlorine exists at high pH (>9), strongly absorbs light at 290 nm. This paper describes the systematic approach that is used in the modelling and design of this sensor system. It also outlines the construction of the device and gives an evaluation of the performance in the laboratory environment.
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paper_title: Solid Electrolyte CO2 Sensor Using NASICON and Li-based Binary Carbonate Electrode

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A solid electrolyte CO2 sensor was developed by combining an Na+ conductor and a Li-based binary carbonate auxiliary electrode represented by Li2CO3–CaCO3 (1.8 : 1 in molar ratio: eutectic mixture). It responded to CO2 quickly and reversibly, following a Nernst equation excellently in the CO2 concentration range 102–105 ppm. In addition, Li2CO3–CaCO3 electrode was found to be stable to deliquescence even when kept under a highly humid condition at 30 °C for more than 700 h.
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paper_title: Free Base Porphyrins as Ionophores for Heavy Metal Sensors

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Two functionalized porphyrins: 5,10,15,20-tetrakis(3,4-dimethoxyphenyl) porphyrin (A) and 5,10,15,20-tetrakis(3-hydroxyphenyl)porphyrin (B) obtained and characterized by us were used as ionophores (I) for preparing PVC-based membrane sensors selective to Ag+, Pb2+ and Cu2+. The membranes were prepared using three different plasticizers: (bis(2-ethylhexyl)sebacate (DOS), dioctylphtalate (DOP), o-nitrophenyl octyl ether (NPOE) and potassium tetrakis(4-chlorophenyl)borate (KTClPB) as additive. The functional parameters (linear concentration range, slope and selectivity) of the sensors with membrane composition: (I:PVC:KTClPB:Plasticizer) in different ratios were investigated. The best results were obtained for the membranes in the ratio I:PVC:KTClPB:Plasticizer 10:165:5:330. The influence of pH on the sensors response was studied. The sensors were used for a period of four months and their utility has been tested on synthetic and real samples.
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paper_title: Study and Production of Organic Phosphorus Sensor Fast Pesticides Detection

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Organic phosphorus sensor has been instrumented with P.V.C as mem brane Carrier mixed with the phosphate andthe electric sensitive matter of organic phosphorus as active component. We have tested the sensor characteristics: the response-time was short (≤20s), the detection minimum is lower than 0.1×10-6 and the selectivity coefficient is lower than 0.1. It wasa kind of convenient and speedy determination instrument for assaying crganic phosphorous pesticides.
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paper_title: Indium oxide-based gas sensor for selective detection of CO

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Among various single-metal oxides, In 2 O 3 , SnO 2 and ZnO were found to exhibit rather high sensitivities to CO at 300°C and above. Especially In 2 O 3 appeared to be most attractive in view of the selectivity to CO over H 2 . It was further found that modifications of In 2 O 3 with the addition of alkali metal carbonates, especially Rb 2 CO 3 , were very effective for enhancing the sensitivity and the selectivity to CO. The sensor element using Rb-In 2 O 3 could detect 500-4000 ppm CO in wet air at 300°C satisfactorily, while its cross-sensitivities to other gases such as H 2 , CH 4, C 3 H 6 , and NO were comparatively small. Catalytic activity test and TPD measurements showed that, as a reason for the promoting effects, the addition of Rb 2 CO 3 to In 2 O 3 enhances the catalytic activity of CO oxidation. In addition, XPS data indicated that, as another reason, Rb 2 CO 3 forms the strongest p-n junctions with In 2 O 3 among alkali metal carbonates.
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paper_title: A Four-Terminal Water-Quality-Monitoring Conductivity Sensor

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In this paper, a new four-electrode sensor for water conductivity measurements is presented. In addition to the sensor itself, all signal conditioning is implemented together with signal processing of the sensor outputs to determine the water conductivity. The sensor is designed for conductivity measurements in the range from 50 mS/m up to 5 S/m through the correct placement of the four electrodes inside the tube where the water flows. The implemented prototype is capable of supplying the sensor with the necessary current at the measurement frequency, acquiring the sine signals across the voltage electrodes of the sensor and across a sampling impedance to determine the current. A temperature sensor is also included in the system to measure the water temperature and, thus, compensate the water-conductivity temperature dependence. The main advantages of the proposed conductivity sensor include a wide measurement range, an intrinsic capability to minimize errors caused by fouling and polarization effects, and an automatic compensation of conductivity measurements caused by temperature variations.
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paper_title: Monitoring chemical plumes in an environmental sensing chamber with a wireless chemical sensor network

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This paper describes the development of a wireless chemical sensor network (WCSN) and an environmental sensing chamber (ESC) within which this WCSN was tested. The WCSN used in this work takes advantage of recent advances in low power wireless communication platforms and novel light emitting diode (LED) based chemical sensing techniques. Plumes of acetic acid were employed for testing and were detected by LED based colorimetric acid responsive chemical sensors. Wireless sensor nodes were positioned in fixed locations within the chamber and responses to plumes of acetic acid were monitored. Preliminary test data show that sensor response time and magnitude are related to sensor position and plume profile, and by operating the sensors collectively in a WCSN it was possible to track chemical plumes in real-time as they moved through the chamber. We envisage that it will be possible to use chemical sensors arranged in a WCSN such as this to map and predict chemical plume dynamics.
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paper_title: Undersea wireless sensor network for ocean pollution prevention

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The ability to effectively communicate underwater has numerous applications, such as oceanographic data collection, pollution monitoring, disaster prevention, assisted navigation, tactical surveillance applications, and exploration of natural underwater sea resources. In this paper, we have developed a completely decentralized ad-hoc wireless sensor network for the ocean pollution detection. We mainly emphasize on the deployment of sensors, protocol stack, the synchronization algorithm and the routing algorithm in order to maximize the lifetime of the network and also to improve its Quality of Service (QoS).
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paper_title: Underwater sensor networks: applications, advances and challenges

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This paper examines the main approaches and challenges in the design and implementation of underwater wireless sensor networks. We summarize key applications and the main phenomena related to acoustic propagation, and discuss how they affect the design and operation of communication systems and networking protocols at various layers. We also provide an overview of communications hardware, testbeds and simulation tools available to the research community.
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paper_title: A Water Pollution Detective System Based on Wireless Sensor Network

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Traditional water pollution detecting methods are time-consuming and complex.Therefore,an on-line detecting method using the wireless sensor networks for detecting water index real-time is proposed.WSNs nodes are installed in waters to be detected,and GPRS is used to transmit the collected data.Management query technology for WSNs communication Nodes(backbone nodes) based on the Internet is used to display platform which can improve the system capability of detecting and automation.The energy-saving routing zigbee protocol of the wireless sensor networks(WSNs) is discussed,and the system hardware and software are designed.The simulated experiment results show the proposed system can realize the reliable and high-speed communication between the remote control center and WSNs.The system is suitable for site polluted water continuous monitoring because of its small size and low cost.
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paper_title: Underwater Acoustic Sensor Networks: Research Challenges

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Underwater sensor nodes will find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance applications. Moreover, unmanned or autonomous underwater vehicles (UUVs, AUVs), equipped with sensors, will enable the exploration of natural undersea resources and gathering of scientific data in collaborative monitoring missions. Underwater acoustic networking is the enabling technology for these applications. Underwater networks consist of a variable number of sensors and vehicles that are deployed to perform collaborative monitoring tasks over a given area. In this paper, several fundamental key aspects of underwater acoustic communications are investigated. Different architectures for two-dimensional and three-dimensional underwater sensor networks are discussed, and the characteristics of the underwater channel are detailed. The main challenges for the development of efficient networking solutions posed by the underwater environment are detailed and a cross-layer approach to the integration of all communication functionalities is suggested. Furthermore, open research issues are discussed and possible solution approaches are outlined. � 2005 Published by Elsevier B.V.
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paper_title: Development and Application of a Next Generation Air Sensor Network for the Hong Kong Marathon 2015 Air Quality Monitoring

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This study presents the development and evaluation of a next generation air monitoring system with both laboratory and field tests. A multi-parameter algorithm was used to correct for the impact of environmental conditions on the electrochemical sensors for carbon monoxide (CO) and nitrogen dioxide (NO2) pollutants. The field evaluation in an urban roadside environment in comparison to designated monitors showed good agreement with measurement error within 5% of the pollutant concentrations. Multiple sets of the developed system were then deployed in the Hong Kong Marathon 2015 forming a sensor-based network along the marathon route. Real-time air pollution concentration data were wirelessly transmitted and the Air Quality Health Index (AQHI) for the Green Marathon was calculated, which were broadcast to the public on an hourly basis. The route-specific sensor network showed somewhat different pollutant patterns than routine air monitoring, indicating the immediate impact of traffic control during the marathon on the roadside air quality. The study is one of the first applications of a next generation sensor network in international sport events, and it demonstrated the usefulness of the emerging sensor-based air monitoring technology in rapid network deployment to supplement existing air monitoring.
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paper_title: The detection of evaporating hazardous material released from moving sources using a gas sensor network

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Abstract Sensor information resulting from distributed locations and/or a multitude of instruments and heterogeneous sensors can increase the reliability of safety and security applications. A gas-sensing platform was developed, communicating via a wireless sensor network based on IEEE 802.15.4 and/or Ethernet. Data from this network are aggregated via a central server feeding its information via TCP/IP into subsequent data fusion software. The usually limited spatio-temporal resolution of chemical sensors can be compensated by space-time sensor data fusion. Sensor nodes have been equipped with metal oxide gas sensors in order to identify hazardous materials [1] . A number of these nodes have then been placed alongside a corridor people had to pass to enter a restricted area. The data from the chemical sensors were fused with tracking data from laser range scanners and video systems. It has been shown that it was possible to allocate a chemical contamination of one individual within a group of moving people and discriminate between various fire accelerating fuels and solvents. This was successfully demonstrated outside the laboratory with a test corridor build in a tent during a military tech-demo in Eckernforde, Germany.
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paper_title: Design of a Water Environment Monitoring System Based on Wireless Sensor Networks

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A water environmental monitoring system based on a wireless sensor network is proposed. It consists of three parts: data monitoring nodes, data base station and remote monitoring center. This system is suitable for the complex and large-scale water environment monitoring, such as for reservoirs, lakes, rivers, swamps, and shallow or deep groundwaters. This paper is devoted to the explanation and illustration for our new water environment monitoring system design. The system had successfully accomplished the online auto-monitoring of the water temperature and pH value environment of an artificial lake. The system's measurement capacity ranges from 0 to 80 °C for water temperature, with an accuracy of ±0.5 °C; from 0 to 14 on pH value, with an accuracy of ±0.05 pH units. Sensors applicable to different water quality scenarios should be installed at the nodes to meet the monitoring demands for a variety of water environments and to obtain different parameters. The monitoring system thus promises broad applicability prospects.
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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: SmartCoast: A Wireless Sensor Network for Water Quality Monitoring

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The implementation of the Water Framework Directive (WFD) across the EU, and the growing international emphasis on the management of water quality is giving rise to an expanding market for novel, miniaturized, intelligent monitoring systems for freshwater catchments, transitional and coastal waters. This paper describes the "SmartCoast" multi sensor system for water quality monitoring. This system is aimed at providing a platform capable of meeting the monitoring requirements of the Water Framework Directive. The key parameters under investigation include temperature, phosphate, dissolved oxygen, conductivity, pH, turbidity and water level. The "plug and play" capabilities enabled by the wireless sensor network (WSN) platform developed at Tyndall allow for integration of sensors as required are described, as well as the custom sensors under development within the project.
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paper_title: A Remote Wireless Sensor Networks for Water Quality Monitoring

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To resolve real-time the traditional water quality detection method, a novel system of remote water quality measuring and monitoring based on wireless sensor network (WSN) and Code Division Multiple Access (CDMA) technology is proposed. The WSNs can monitor the targets and water quality information of the waters through the cooperation of a large amount of sensors. The optimization of node distribution is studied with the intention of reducing the energy consumption and ensuring the effective information acquisition in wireless sensor network. The functions of remote detection and real-time monitoring of natural water are implemented through the CDMA wireless data transmission. This system has a simple architecture, and isn’t confined by the geographical position. The experimental results show that this system can run stably, and its operation is convenient.
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paper_title: Wireless sensor network for real-time air pollution monitoring

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This paper presents an ambient real-time air quality monitoring system. The system consists of several distributed monitoring stations that communicate wirelessly with a backend server using machine-to-machine communication. Each station is equipped with gaseous and meteorological sensors as well as data logging and wireless communication capabilities. The backend server collects real time data from the stations and converts it into information delivered to users through web portals and mobile applications. The system is implemented in pilot phase and four solar-powered stations are deployed over an area of 1 km2. Data over four months has been collected and performance analysis and assessment are performed. As the historical data bank becomes richer, more sophisticated operations can be performed.
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paper_title: Gas sensor network for air-pollution monitoring

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This paper describes the development of a gas sensor system to be used as a sensing node to form a dense real-time environmental monitoring network. Moreover, a new auto-calibration method is proposed to achieve the maintenance-free operation of the sensor network. The network connectivity can be used not only for data collection but also for the calibration and diagnosis of the sensors since the measured pollutant concentrations can be easily compared through the network with nearby sensors and governmental monitoring stations. Different pollutant concentrations are usually monitored at different sites. However, a case study on local NO2 distribution has shown that there exists a special condition under which pollutant concentrations become low and uniform in a certain local area. The baseline of the gas sensor response can be adjusted in this special occasion using the pollutant concentration values reported from the neighboring environmental monitoring stations. The experimental result has shown that NO2 concentration can be measured with sufficient accuracy by incorporating appropriate temperature and humidity compensation into calibration curves. Moreover, a case study on auto-calibration demonstrates its effectiveness in keeping the measurement accuracy of the sensor system in long-term operation.
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paper_title: A 3D miniaturised programmable transceiver

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Purpose – To describe the development of a three dimensional programmable transceiver system of modular design for use as a development tool for a variety of wireless sensor node applications.Design/methodology/approach – As a stepping‐stone towards the development of wireless nodes, sensor networks programme was put in place to develop a 25 mm cube module, which was modular in construction, programmable and miniaturised in form factor. This was to facilitate the development of wireless sensor networks for a variety of different applications. The nodes are used as a platform for sensing and actuating through various parameters, for use in scalable, reconfigurable distributed autonomous sensing networks in a number of research projects currently underway in the Tyndall Institute, as well as other institutes and in a variety of research programs in the area of wireless sensor networks.Findings – The modular construction enables the heterogeneous implementation of a variety of technologies required in the ar...
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paper_title: Multi-hop Reliability and Network Operation Routing

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Many routing, power aware and data diffusion protocols have been designed especially for WSN, which are reliability and network operation based. The presentation of various ideas on multi-hop reliability and network operation based routing protocols is given here. Unattended sensor nodes deployed randomly in the network area require reliable routing. In recent years, an extensive research has addressed various issues for the coordination and management of nodes for efficient operations and efficient routing. The mission of maintaining and finding routes is nontrivial as sudden changes in status of nodes lead to unpredictable consequences. In this chapter, comparative study of various routing protocols has been presented to pave new ways to researchers. In this chapter, we have classified reliability and network operation routing in to five types (i) coherent based, (ii) QoS based, (iii) multipath based, (iv) query based and negotiation based.
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paper_title: Applications of Wireless Sensor Networks in Marine Environment Monitoring: A Survey

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With the rapid development of society and the economy, an increasing number of human activities have gradually destroyed the marine environment. Marine environment monitoring is a vital problem and has increasingly attracted a great deal of research and development attention. During the past decade, various marine environment monitoring systems have been developed. The traditional marine environment monitoring system using an oceanographic research vessel is expensive and time-consuming and has a low resolution both in time and space. Wireless Sensor Networks (WSNs) have recently been considered as potentially promising alternatives for monitoring marine environments since they have a number of advantages such as unmanned operation, easy deployment, real-time monitoring, and relatively low cost. This paper provides a comprehensive review of the state-of-the-art technologies in the field of marine environment monitoring using wireless sensor networks. It first describes application areas, a common architecture of WSN-based oceanographic monitoring systems, a general architecture of an oceanographic sensor node, sensing parameters and sensors, and wireless communication technologies. Then, it presents a detailed review of some related projects, systems, techniques, approaches and algorithms. It also discusses challenges and opportunities in the research, development, and deployment of wireless sensor networks for marine environment monitoring.
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paper_title: Environmental Monitoring System with Wireless Mesh Network Based on Embedded System

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A kind of environmental monitoring system based on wireless mesh network with the core of embedded system ARM9 S3C2410 microprocessor is presented in the paper. The flexible and self-organizing wireless mesh network is used to achieve the real time acquisition and multi-hop wireless communication of parameters of the monitoring atmospheric environment such as SO2, NO2, NO, temperature, humidity and air pressure, etc. The network structure of the system is established, the hardware architecture of the system is designed, and the system working procedures is given. The entire monitoring system can be quickly arranged and rapidly withdrew without support of base station and has a strong self-healing capability and network robustness and can be used for a variety of occasional atmospheric environmental monitoring.
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paper_title: Sensor-based air-pollution measurement system for environmental monitoring network

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Metropolitan cities in the world have long been suffering from serious air pollution problems. In Tokyo, the high levels of nitrogen oxides and ozone resulting from heavy traffic emission are of the greatest concern. However, the cost and size of the chemical analyzers have limited the number of environmental monitoring stations and, therefore, have resulted in insufficient spatial resolution in the measurement of pollutant distributions. The authors have been proposing a gas distribution analyzing system (GASDAS). The use of gas sensors enables compact and inexpensive sensing systems, and will lead to a significant increase in the density of monitoring sites. As a first step in the development of GASDAS, nitrogen dioxide and ozone monitoring systems have been developed. The experimental results have shown that the low-cost sensor systems with signal compensation features for the change in weather conditions can be used for the quantitative measurement of spatial pollutant distributions.
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paper_title: Design and Deployment of a Remote Robust Sensor Network: Experiences from an Outdoor Water Quality Monitoring Network

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This paper investigates a wireless sensor network deployment - monitoring water quality, e.g. salinity and the level of the underground water table - in a remote tropical area of northern Australia. Our goal is to collect real time water quality measurements together with the amount of water being pumped out in the area, and investigate the impacts of current irrigation practice on the environments, in particular underground water salination. This is a challenging task featuring wide geographic area coverage (mean transmission range between nodes is more than 800 meters), highly variable radio propagations, high end-to-end packet delivery rate requirements, and hostile deployment environments. We have designed, implemented and deployed a sensor network system, which has been collecting water quality and flow measurements, e.g., water flow rate and water flow ticks for over one month. The preliminary results show that sensor networks are a promising solution to deploying a sustainable irrigation system, e.g., maximizing the amount of water pumped out from an area with minimum impact on water quality.
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paper_title: Monitoring water quality through a telematic sensor network and a fuzzy expert system

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: In this paper we present an expert system that monitors seawater quality and pollution in northern Greece through a sensor network called Andromeda. The expert system monitors sensor data collected by local monitoring stations and reasons about the current level of water suitability for various aquatic uses, such as swimming and piscicultures. The aim of the expert system is to help the authorities in the decision-making process in the battle against pollution of the aquatic environment, which is vital for public health and the economy of northern Greece. The expert system determines, using fuzzy logic, when certain environmental parameters exceed certain pollution limits, which are specified either by the authorities or by environmental scientists, and flags up appropriate alerts.
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paper_title: Design of a Wireless Sensor Network for Long-term, In-Situ Monitoring of an Aqueous Environment

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An aqueous sensor network is described consisting of an array of sensor nodes that can be randomly distributed throughout a lake or drinking water reservoir. The data of an individual node is transmitted to the host node via acoustic waves using intermediate nodes as relays. Each node of the sensor network is a data router, and contains sensors capable of measuring environmental parameters of interest. Depending upon the required application, each sensor node can be equipped with different types of physical, biological or chemical sensors, allowing long-term, wide area, in situ multi-parameter monitoring. In this work the aqueous sensor network is described, with application to pH measurement using magnetoelastic sensors. Beyond ensuring drinking water safety, possible applications for the aqueous sensor network include advanced industrial process control, monitoring of aquatic biological communities, and monitoring of waste-stream effluents.
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paper_title: Design and Development of a Wireless Sensor Network Framework for Water Quality Remote Monitoring

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This study involves the design and development of a wireless sensor network (WSN) that integrates several sensing modules into a fully-functional system. The overall system is composed of a remote server, a controller node, and several sensing modules. The controller node is implemented using an Android mobile phone with Bluetooth and 3G capabilities. Bluetooth is used to communicate with the various sensing modules; while 3G is used to relay data to the remote server. The sensing modules utilize an Arduino Mega 2560 (with the sensor circuits) and a Bluetooth shield. Test results show that this framework is a viable design for WSN systems and can be used for remote installations that can be continuously upgraded over time.
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paper_title: Group-based underwater wireless sensor network for marine fish farms

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The amount of uneaten feed and fecal waste generated by the fish in marine fish farms causes the damage of the fauna and flora, and it also reduces the economic benefits because the wastage of the uneaten food. In this paper, we propose an underwater group-based sensor network in order to quantify accurately the amount of pollution deposited on the seabed. First, an analytical model let us know the best location to place the sensor nodes. Our group-based wireless sensor network (WSN) proposal could also determine the amount of food that is wasted while it measures the amount of deposits generated. We describe the mobility of the nodes and how operates the group-based protocol and we show several simulations in order to view the load traffic and to verify the correct operation of the WSN.
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paper_title: Ultra low power Wireless Gas Sensor Network for environmental monitoring applications

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We present an environmental monitoring system based on wireless sensor network for air quality measurement and natural gas leakages. The system is based on catalytic off-the-self available gas sensors and on a novel strategy of sampling and processing which permits to reduce the energy consumption of one order of magnitude. The characteristic of the sensing device has been extracted both with the standard utilization and the new proposed approach, to compare and validate our results. Moreover the importance of the humidity present in the environment has been taken into account and included in the model, because it severely affects the measurements. The wireless sensor network developed has been also extended using a smartphone to enable data sharing over internet and to enhance portability of the overall system.
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paper_title: Development of wireless sensor network for combustible gas monitoring

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a b s t r a c t This paper describes the development and the characterization of a wireless gas sensor network (WGSN) for the detection of combustible or explosive gases. The WGSN consists of a sensor node, a relay node, a network coordinator, and a wireless actuator. The sensor node attains early gas detection using an on board 2D semiconductor sensor. Because the sensor consumes a substantial amount of power, which negatively affects the node lifetime, we employ a pulse heating profile to achieve significant energy savings. The relay node receives and forwards traffic from sensor nodes towards the network coordinator and vice versa. When an emergency is detected, the network coordinator alarms an operator through the GSM/GPRS or Ethernet network, and may autonomously control the source of gas emission through the wireless actuator. Our experimental results demonstrate how to determine the optimal temperature of the sensor's sensitive layer for methane detection, show the response time of the sensor to various gases, and evaluate the power consumption of the sensor node. The demonstrated WGSN could be used for a wide range of gas monitoring applications.
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paper_title: Dynamic gas sensor network for air pollution monitoring and its auto-calibration

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The use of a dynamic gas sensor network is proposed for air pollution monitoring, and its auto-calibration is discussed to achieve the maintenance-free operation. Although the gas sensor outputs generally show drift over time, frequent recalibration of a number of sensors in the network is a laborious task. To solve this problem, instead of the static network proposed in the related works, we propose to realize a dynamic gas sensor network by, e.g., placing sensors on vehicles running on the streets or placing some of them at fixed points and the others on vehicles. Since each sensor in the dynamic network often meets other sensors, calibration of that specific sensor can be performed by comparing the sensor outputs in such occasions. The sensors in the whole network can thus be calibrated eventually. The simulation results are presented to show that adjusting the sensor outputs to the average values of the sensors sharing the same site improves the measurement accuracy of the sensor network.
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paper_title: Detecting and estimating biochemical dispersion of a moving source in a semi-infinite medium

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Statistical methods for detecting and estimating biochemical dispersion by a moving source using model-based integrated sensor array processing are developed. Two possible cases are considered: a homogeneous semi-infinite medium (corresponding to the environment such as air above the ground for an airborne source) or a two-layer semi-infinite medium (e.g., shallow water). The proposed methods can be extended to more complex scenarios. The goals are to detect and localize the biochemical source, determine the space-time concentration distribution of the dispersion, and predict its cloud evolution. Potential applications include security, environmental monitoring, pollution control, simulating hazardous accidents, and explosives detection. Diffusion models of the biochemical substance concentration distribution are derived under various boundary and environmental conditions. A maximum-likelihood algorithm is used to estimate the biochemical concentration distribution in space and time, and the Cramer-Rao bound is computed to analyze its performance. Two detectors (generalized-likelihood ratio test (GLRT) and a mean-difference detector) are derived and then their performances are determined in terms of the probabilities of detection and false alarm. The results can be used to design the sensor array for optimal performance. Numerical examples illustrate the results of the concentration distribution and the performances of the proposed methods.
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paper_title: A Study on Water Pollution Source Localization in Sensor Networks

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The water pollution source localization is of great significance to water environment protection. In this paper, a study on water pollution source localization is presented. Firstly, the source detection is discussed. Then, the coarse localization methods and the localization methods based on diffusion models are introduced and analyzed, respectively. In addition, the localization method based on the contour is proposed. The detection and localization methods are compared in experiments finally. The results show that the detection method using hypotheses testing is more stable. The performance of the coarse localization algorithm depends on the nodes density. The localization based on the diffusion model can yield precise localization results; however, the results are not stable. The localization method based on the contour is better than the other two localization methods when the concentration contours are axisymmetric. Thus, in the water pollution source localization, the detection using hypotheses testing is more preferable in the source detection step. If concentration contours are axisymmetric, the localization method based on the contour is the first option. And, in case the nodes are dense and there is no explicit diffusion model, the coarse localization algorithm can be used, or else the localization based on diffusion models is a good choice.
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paper_title: Water Pollution Detection Based on Hypothesis Testing in Sensor Networks

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Water pollution detection is of great importance in water conservation. In this paper, the water pollution detection problems of the network and of the node in sensor networks are discussed. The detection problems in both cases of the distribution of the monitoring noise being normal and nonnormal are considered. The pollution detection problems are analyzed based on hypothesis testing theory firstly; then, the specific detection algorithms are given. Finally, two implementation examples are given to illustrate how the proposed detection methods are used in the water pollution detection in sensor networks and prove the effectiveness of the proposed detection methods.
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paper_title: Distributed Sequential Bayesian Estimation of a Diffusive Source in Wireless Sensor Networks

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We develop an efficient distributed sequential Bayesian estimation method for applications relating to diffusive sources-localizing a diffusive source, determining its space-time concentration distribution, and predicting its cloud envelope evolution using wireless sensor networks. Potential applications include security, environmental and industrial monitoring, as well as pollution control. We first derive the physical model of the substance dispersion by solving the diffusion equations under different environment scenarios and then integrate the physical model into the distributed processing technologies. We propose a distributed sequential Bayesian estimation method in which the state belief is transmitted in the wireless sensor networks and updated using the measurements from the new sensor node. We propose two belief representation methods: a Gaussian density approximation and a new LPG function (linear combination of polynomial Gaussian density functions) approximation. These approximations are suitable for the distributed processing in wireless sensor networks and are applicable to different sensor network situations. We implement the idea of information-driven sensor collaboration and select the next sensor node according to certain criterions, which provides an optimal subset and an optimal order of incorporating the measurements into our belief update, reduces response time, and saves energy consumption of the sensor network. Numerical examples demonstrate the effectiveness and efficiency of the proposed methods
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paper_title: Plume Source Position Estimation Using Sensor Networks

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This paper proposes the use of a sensor network for estimating the location of a source that releases certain substance in the environment which is then propagated over a large area. More specifically, we use nonlinear least squares optimization to estimate the source position based on the concentration readings at the sensor nodes. Such a network can be of tremendous help to emergency personnel trying to protect people from terrorist attacks or responding to an accident. Our results indicate that in high uncertainty environments it pays off to use a large number of sensors in the estimation whereas in low uncertainty scenarios a few sensors achieve satisfactory results. In addition, our results point out the importance of choosing the appropriate parameters for the least squares optimization especially the start position for our algorithm. We compare our results to the closest point approach (CPA) where the source location is assumed to be the sensor node with the highest measurement
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paper_title: Water pollution source localization based on the contour in sensor networks

paper_content:

To make up the shortcomings of the coarse pollution source localization algorithm and the localization methods based on the diffusion models in water, a pollution source localization algorithm based on the concentration contour is proposed. In the method, the location of the source is obtained according to the geometrical configuration feature of the contour. In the simulations, based on the simulation data of MODFLOW, the proposed localization method is tested and compared with the localization methods based on diffusion models and the CPA(Closest Point Approach) localization method. The results show that the performance of the proposed algorithm is better than the other two methods when the concentration contour is axisymmetric.
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paper_title: Plume Source Position Estimation Using Sensor Networks

paper_content:

This paper proposes the use of a sensor network for estimating the location of a source that releases certain substance in the environment which is then propagated over a large area. More specifically, we use nonlinear least squares optimization to estimate the source position based on the concentration readings at the sensor nodes. Such a network can be of tremendous help to emergency personnel trying to protect people from terrorist attacks or responding to an accident. Our results indicate that in high uncertainty environments it pays off to use a large number of sensors in the estimation whereas in low uncertainty scenarios a few sensors achieve satisfactory results. In addition, our results point out the importance of choosing the appropriate parameters for the least squares optimization especially the start position for our algorithm. We compare our results to the closest point approach (CPA) where the source location is assumed to be the sensor node with the highest measurement
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paper_title: A Study on Water Pollution Source Localization in Sensor Networks

paper_content:

The water pollution source localization is of great significance to water environment protection. In this paper, a study on water pollution source localization is presented. Firstly, the source detection is discussed. Then, the coarse localization methods and the localization methods based on diffusion models are introduced and analyzed, respectively. In addition, the localization method based on the contour is proposed. The detection and localization methods are compared in experiments finally. The results show that the detection method using hypotheses testing is more stable. The performance of the coarse localization algorithm depends on the nodes density. The localization based on the diffusion model can yield precise localization results; however, the results are not stable. The localization method based on the contour is better than the other two localization methods when the concentration contours are axisymmetric. Thus, in the water pollution source localization, the detection using hypotheses testing is more preferable in the source detection step. If concentration contours are axisymmetric, the localization method based on the contour is the first option. And, in case the nodes are dense and there is no explicit diffusion model, the coarse localization algorithm can be used, or else the localization based on diffusion models is a good choice.
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paper_title: Gas detection and source localization: A Bayesian approach

paper_content:

This paper discusses modeling solutions that support detection of gaseous chemical substances and source localization in applications that are characterized by large numbers of noisy information sources, absence of calibrated concentration measurements and lack of detailed knowledge about the physical processes. In particular, we introduce a solution based on discrete Bayesian networks which allows tractable exploitation of large quantities of spatio-temporally distributed heterogeneous observations. The emphasis is on using coarse models avoiding assumptions about detailed aspects of the gas propagation processes. By considering properties of Bayesian networks we discuss the consequences of modeling simplifications and show with the help of simulations that the resulting inference processes are robust with respect to the modeling deviations.
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paper_title: Biochemical Transport Modeling and Bayesian Source Estimation in Realistic Environments

paper_content:

Early detection and estimation of the spread of a biochemical contaminant are major issues in many applications, such as homeland security and pollution monitoring. We present an integrated approach combining the measurements given by an array of biochemical sensors with a physical model of the dispersion and statistical analysis to solve these problems and provide system performance measures. We approximate the dispersion model of a contaminant in a realistic environment through numerical simulations of reflected stochastic diffusions describing the microscopic transport phenomena due to wind and chemical diffusion and use the Feynmann-Kac formula. We consider arbitrary complex geometries and account for wind turbulence. Numerical examples are presented for two real-world scenarios: an urban area and an indoor ventilation duct. Localizing the dispersive sources is useful for decontamination purposes and estimation of the cloud evolution. To solve the associated inverse problem, we propose a Bayesian framework based on a random field that is particularly powerful for localizing multiple sources with small amounts of measurements
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paper_title: Estimation of Pollutant-Emitting Point-Sources using Resource-Constrained Sensor Networks

paper_content:

We present an algorithm that makes an appropriate use of a Kalman filter combined with a geometric computation with respect to the localisation of a pollutant-emitting point source. Assuming resource-constrained inexpensive nodes and no specific placement distance to the source, our approach has been shown to perform well in estimating the coordinates and intensity of a source. Using local gossip to directionally propagate estimates, our algorithm initiates a real-time exchange of information that has as an ultimate goal to lead a packet from a node that initially sensed the event to a destination that is as close to the source as possible. The coordinates and intensity measurement of the destination comprise the final estimate. In this paper, we assert that this low-overhead coarse localisation method can rival more sophisticated and computationally-hungry solutions to the source estimation problem.
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paper_title: Plume Source Localizing in Different Distributions and Noise Types Based on WSN

paper_content:

Accidental gas leaks from unknown sites will cause the serious environmental pollution. One of the efficient methods to solve the problem is tracking and locating the plume source position. This paper presents a wireless sensor network installed with the gas sensor to on-line monitor the environment and estimate the location of a gas source based on the concentration readings at the wireless sensor nodes. Nonlinear Least Squares Method (NLS) was proposed for localization. The effect of the estimation error, with different distributions of the sensor nodes, different sensor number and different types of the back ground noises, is researched by simulations. The simulation results show that when the number of the nodes is more, the effect of the different distributions is not distinct. While the number of the nodes is less, the estimation error under the uniform distribution is more stable than under the random distribution. The suitable deployed method is discussed based on the simulation results. We also discussed the impact of the different noise types to the estimation error.
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paper_title: Distributed Sequential Bayesian Estimation of a Diffusive Source in Wireless Sensor Networks

paper_content:

We develop an efficient distributed sequential Bayesian estimation method for applications relating to diffusive sources-localizing a diffusive source, determining its space-time concentration distribution, and predicting its cloud envelope evolution using wireless sensor networks. Potential applications include security, environmental and industrial monitoring, as well as pollution control. We first derive the physical model of the substance dispersion by solving the diffusion equations under different environment scenarios and then integrate the physical model into the distributed processing technologies. We propose a distributed sequential Bayesian estimation method in which the state belief is transmitted in the wireless sensor networks and updated using the measurements from the new sensor node. We propose two belief representation methods: a Gaussian density approximation and a new LPG function (linear combination of polynomial Gaussian density functions) approximation. These approximations are suitable for the distributed processing in wireless sensor networks and are applicable to different sensor network situations. We implement the idea of information-driven sensor collaboration and select the next sensor node according to certain criterions, which provides an optimal subset and an optimal order of incorporating the measurements into our belief update, reduces response time, and saves energy consumption of the sensor network. Numerical examples demonstrate the effectiveness and efficiency of the proposed methods
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paper_title: Plume Source Position Estimation Using Sensor Networks

paper_content:

This paper proposes the use of a sensor network for estimating the location of a source that releases certain substance in the environment which is then propagated over a large area. More specifically, we use nonlinear least squares optimization to estimate the source position based on the concentration readings at the sensor nodes. Such a network can be of tremendous help to emergency personnel trying to protect people from terrorist attacks or responding to an accident. Our results indicate that in high uncertainty environments it pays off to use a large number of sensors in the estimation whereas in low uncertainty scenarios a few sensors achieve satisfactory results. In addition, our results point out the importance of choosing the appropriate parameters for the least squares optimization especially the start position for our algorithm. We compare our results to the closest point approach (CPA) where the source location is assumed to be the sensor node with the highest measurement
---
paper_title: Wireless sensor network for real-time air pollution monitoring

paper_content:

This paper presents an ambient real-time air quality monitoring system. The system consists of several distributed monitoring stations that communicate wirelessly with a backend server using machine-to-machine communication. Each station is equipped with gaseous and meteorological sensors as well as data logging and wireless communication capabilities. The backend server collects real time data from the stations and converts it into information delivered to users through web portals and mobile applications. The system is implemented in pilot phase and four solar-powered stations are deployed over an area of 1 km2. Data over four months has been collected and performance analysis and assessment are performed. As the historical data bank becomes richer, more sophisticated operations can be performed.
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paper_title: Parameter estimation of a continuous chemical plume source

paper_content:

The problem is estimation of the strength (emission rate) and the location of a chemical source from which a contaminant is released continuously into the atmosphere. The concentration of the contaminant is measured at regular intervals by a network of spatially distributed chemical sensors. The transport of the contaminant is modeled by turbulent diffusion and fluctuating plume concentration. The source parameter estimation is solved in the sequential Bayesian framework, with the posterior expectation approximated using Monte Carlo integration. In order to deal with the vague prior, importance sampling is implemented using the progressive correction technique. The paper presents numerical analysis of statistical performance of the proposed algorithms for different sensor configurations.
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paper_title: A Study on Water Pollution Source Localization in Sensor Networks

paper_content:

The water pollution source localization is of great significance to water environment protection. In this paper, a study on water pollution source localization is presented. Firstly, the source detection is discussed. Then, the coarse localization methods and the localization methods based on diffusion models are introduced and analyzed, respectively. In addition, the localization method based on the contour is proposed. The detection and localization methods are compared in experiments finally. The results show that the detection method using hypotheses testing is more stable. The performance of the coarse localization algorithm depends on the nodes density. The localization based on the diffusion model can yield precise localization results; however, the results are not stable. The localization method based on the contour is better than the other two localization methods when the concentration contours are axisymmetric. Thus, in the water pollution source localization, the detection using hypotheses testing is more preferable in the source detection step. If concentration contours are axisymmetric, the localization method based on the contour is the first option. And, in case the nodes are dense and there is no explicit diffusion model, the coarse localization algorithm can be used, or else the localization based on diffusion models is a good choice.
---
paper_title: Plume Source Localization Based on Bayes Using Wireless Sensor Network

paper_content:

A wireless sensor network(WSN) was introduced into predicted evaluation of plume source localization.Based on the Bayes principle,an improved particle filter(IPF) algorithm was proposed,which is adapted for the gas pollution source localization using WSN.It was used to improve the filter performance that the methods of the weighted centraid,the backoff timer sorting and the residual resampling were adopted to determine the initial point of predicted location,the information sorting of located node and reduce the sampling variance respectively.The comparison of the simulated location performances among the IPF,the extended Kalman filter(EKF) and the improved non-linear least square(I-NLS) shows that WSN is effective on the plume source localization;IPF is better than EKF and I-NLS.
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paper_title: Stochastic algorithm for estimation of the model's unknown parameters via Bayesian inference

paper_content:

We have applied the methodology combining Bayesian inference with Markov chain Monte Carlo (MCMC) algorithms to the problem of the atmospheric contaminant source localization. The algorithms input data are the on-line arriving information about concentration of given substance registered by sensors' network. A fast-running Gaussian plume dispersion model is adopted as the forward model in the Bayesian inference approach to achieve rapid-response event reconstructions and to benchmark the proposed algorithms. We examined different version of the MCMC in effectiveness to estimate the probabilistic distributions of atmospheric release parameters by scanning 5-dimensional parameters' space. As the results we obtained the probability distributions of a source coordinates and dispersion coefficients which we compared with the values assumed in creation of the sensors' synthetic data. The annealing and burn-in procedures were implemented to assure a robust and efficient parameter-space scans.
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paper_title: On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds

paper_content:

We consider a new algorithm, an interior-reflective Newton approach, for the problem of minimizing a smooth nonlinear function of many variables, subject to upper and/or lower bounds on some of the variables. This approach generatesstrictly feasible iterates by using a new affine scaling transformation and following piecewise linear paths (reflection paths). The interior-reflective approach does not require identification of an "activity set". In this paper we establish that the interior-reflective Newton approach is globally and quadratically convergent. Moreover, we develop a specific example of interior-reflective Newton methods which can be used for large-scale and sparse problems.
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paper_title: An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds

paper_content:

We propose a new trust region approach for minimizing nonlinear functions subject to simple bounds. By choosing an appropriate quadratic model and scaling matrix at each iteration, we show that it is not necessary to solve a quadratic programming subproblem, with linear inequalities, to obtain an improved step using the trust region idea. Instead, a solution to a trust region subproblem is defined by minimizing a quadratic function subject only to an ellipsoidal constraint. The iterates generated by these methods are always strictly feasible. Our proposed methods reduce to a standard trust region approach for the unconstrained problem when there are no upper or lower bounds on the variables. Global and quadratic convergence of the methods is established; preliminary numerical experiments are reported.
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paper_title: Bayesian source detection and parameter estimation of a plume model based on sensor network measurements

paper_content:

We consider a network of sensors that measure the intensities of a complex plume composed of multiple absorption–diffusion source components. We address the problem of estimating the plume parameters, including the spatial and temporal source origins and the parameters of the diffusion model for each source, based on a sequence of sensor measurements. The approach not only leads to multiple-source detection, but also the characterization and prediction of the combined plume in space and time. The parameter estimation is formulated as a Bayesian inference problem, and the solution is obtained using a Markov chain Monte Carlo algorithm. The approach is applied to a simulation study, which shows that an accurate parameter estimation is achievable. Copyright © 2010 John Wiley & Sons, Ltd. ::: ::: A preliminary version of this work was presented at 9th ONR-GTRI Workshop on Target Tracking in Sensor Fusion, 2006.
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paper_title: Offshore Pollution Source Localization in Static Water Using Wireless Sensor Networks

paper_content:

In water environments such as water reservoirs and lakes, the diffusion of pollutants is affected by boundaries.Firstly, the offshore plume source diffusion in static water is analysed and a piecewise concentration model is proposed.The localization of the pollution source near an impervious boundary is studied. It is shown that unknown parameters include not only the source position but also the mass flow rate and the initial diffusion time. To estimate the unknown parameters, we provide three algorithms, which are respectively based on a general model, an approximation function and the unscented Kalman filter(UKF). The first two algorithms employ the original concentration model and piecewise concentration model respectively, and estimate the parameters by solving the constrained nonlinear least squares problem.By using the general model based algorithm, source parameters can be acquired promptly. The algorithm based on the approximation function is more robust compared with that on the general model, although it can only be executed for sufficient samples. Considering the diffusion process, the algorithm based on UKF achieves a good tradeoff between the computation complexity and the estimation accuracy. The simulation data are generated by MODFLOW, which is a standard software for the hydrological simulation of source diffusion. Three proposed algorithms are tested by simulation data, and the results demonstrate their advantages and disadvantages.
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paper_title: Application of Sensor Networks in Plume Source Position Estimation

paper_content:

Based on the attenuation model of the plume,the location of plume source using maximum likelihood algorithm and the nonlinear least squares algorithm were studied.The effect of the estimation error,with different sensor number and different back ground noise,is researched by simulation.The(result) shows that better accuracy can be got by using nonlinear squares algorithm when the background noise is less.On the contrary,the maximum likelihood algorithm is robust to the much noise compared with the nonlinear squares algorithm.
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paper_title: Study and Production of Organic Phosphorus Sensor Fast Pesticides Detection

paper_content:

Organic phosphorus sensor has been instrumented with P.V.C as mem brane Carrier mixed with the phosphate andthe electric sensitive matter of organic phosphorus as active component. We have tested the sensor characteristics: the response-time was short (≤20s), the detection minimum is lower than 0.1×10-6 and the selectivity coefficient is lower than 0.1. It wasa kind of convenient and speedy determination instrument for assaying crganic phosphorous pesticides.
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paper_title: Coverage Control in Sensor Networks

paper_content:

This easy-to-read text focuses on challenges in coverage control in sensor networks, examines fundamental coverage problems, and presents the most recent advances and techniques in the field. Features: provides an introduction to sensors, sensor nodes, sensor networks, and sensor coverage models; supplies an informal definition and taxonomy for network-wide coverage control; explores the node placement optimization problem for coverage configuration before network deployment; investigates the coverage lifetime maximization problem by controlling coverage characteristics in a randomly deployed network; discusses the critical sensor-density problem for coverage configuration before network deployment; examines the sensor-activity scheduling problem of controlling network coverage characteristics in a randomly deployed network; introduces the node movement strategy problem for sensor networks containing mobile nodes; presents the challenges of building intrusion barriers and finding penetration paths.
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paper_title: On the Connectivity of Ad Hoc Networks

paper_content:

This paper presents a framework for the calculation of stochastic connectivity properties of wireless multihop networks. Assuming that n nodes, each node with transmission range r0, are distributed according to some spatial probability density function, we study the level of connectivity of the resulting network topology from three viewpoints. First, we analyze the number of neighbors of a given node. Second, we study the probability that there is a communication path between two given nodes. Third, we investigate the probability that the entire network is connected, i.e. each node can communicate with every other node via a multihop path. For the last-mentioned issue, we compute a tight approximation for the critical (r0 ,n )pairs that are required to keep the network connected with a probability close to one. In fact, the problem is solved for the general case of a k-connected network, accounting for the robustness against node failures. These issues are studied for uniformly distributed nodes (with and without ‘border effects’), Gaussian distributed nodes, and nodes that move according to the commonly used random waypoint mobility model. The results are of practical value for the design and simulation of wireless sensor and mobile ad hoc networks.
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paper_title: Problems and challenges in water pollution monitoring and water pollution source localization using sensor networks

paper_content:

Sensor networks have been widely used in environment monitoring. Although there are some related works about water pollution monitoring and water pollution source localization using sensor networks, there are many problems which have not been solved so far. In this paper, the current research status on water pollution monitoring and water pollution source localization in sensor networks is illustrated firstly. And then, the fundamental problems in the researches are analyzed, and the challenges are proposed.
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paper_title: Problems and challenges in water pollution monitoring and water pollution source localization using sensor networks

paper_content:

Sensor networks have been widely used in environment monitoring. Although there are some related works about water pollution monitoring and water pollution source localization using sensor networks, there are many problems which have not been solved so far. In this paper, the current research status on water pollution monitoring and water pollution source localization in sensor networks is illustrated firstly. And then, the fundamental problems in the researches are analyzed, and the challenges are proposed.
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Title: A Survey on Pollution Monitoring Using Sensor Networks in Environment Protection

Section 1: Introduction
Description 1: Introduce the significance of pollution monitoring, the three key problems in it, and the advantages of using sensor networks for environmental protection.

Section 2: Sensors and Networks in Environment Monitoring
Description 2: Discuss the specific types of sensors used for air and water pollution monitoring, the cost implications, and the limitations in practical applications.

Section 3: Sensor Network Systems for Environment Monitoring
Description 3: Describe the structure of environmental monitoring systems, including sensor nodes, data transmission, network topologies, and communication protocols.

Section 4: Pollution Detection Using the Sensor Network
Description 4: Explain the processes and methods used in pollution detection, including coarse detection methods and hypothesis-testing problems.

Section 5: Pollution Source Localization
Description 5: Present physical models of pollutant diffusion, different localization algorithms, and discuss their applicability and performance.

Section 6: Challenges in Environment Monitoring and Pollution Detection
Description 6: Identify and discuss the challenges in sensor technology and communication, and the statistical problems related to pollution detection.

Section 7: Challenges in Pollution Source Localization Using Sensor Networks
Description 7: Discuss the difficulties in dynamic environments, the lack of regularity in pollutant migration, sparse node deployment, and the complexities of diffusion models.

Section 8: Conclusions
Description 8: Summarize the importance of pollution monitoring, review the state-of-the-art in sensor networks for environment monitoring, and outline the presented challenges.