无线传感器网络中英文对照外文翻译文献

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无线传感器网络测距技术外文翻译文献

无线传感器网络测距技术外文翻译文献(文档含中英文对照即英文原文和中文翻译)原文：RANGING TECHNIQUES FOR WIRELESS SENSOR NETWORKSThe RF location sensors operating in different environments can measure the RSS, AOA, phase of arrival (POA), TOA, and signature of the delay - power profile as location metrics to estimate the ranging distance [4,7] . The deployment environment (i.e., wireless RF channel) will constrain the accuracy and the performance of each technique. In outdoor open areas, these ranging techniques perform very well. However, as the wireless medium becomes more complex, for example, dense urban or indoor environments, the channel suffers from severe multipath propagation and heavy shadow fading conditions. This finding in turn impacts the accuracy and performance in estimating the range between a pair of nodes. For this reason, this chapter will focus its ranging and localization discussion on indoor environments. This is important because many of the WSN applications are envisioned for deployment in rough terrain and cluttered environments and understanding of the impact of the channel on the performance of ranging and localization is important. In addition, range measurements using POA and AOA in indoor and urban areas are unreliable. Therefore, we will focus our discussion on two practical techniques,TOA and RSS.These two ranging techniques, which have been used traditionally in wirelessnetworks, have a great potential for use in WSN localization.The TOA based ranging is suitable for accurate indoor localization because it only needs a few references and no prior training. By using this technique, however, the hardware is complex and the accuracy is sensitive to the multipath condition and the system bandwidth. This technique has been implemented in GPS, PinPoint, WearNet, IEEE 802.15.3, and IEEE 802.15.4 systems. The RSS based ranging, on the other hand, is simple to implement and is insensitive to the multipath condition and the bandwidth of the system. In addition, it does not need any synchronization and can work with any existing wireless system that can measure the RSS. For accurate ranging, however, a high density of anchors or reference points is needed and extensive training and computationally expensive algorithms are required.The RSS ranging has been used for WiFi positioning in systems, for example, Ekahau, Newbury Networks, PanGo, and Skyhook.This section first introduces TOA based ranging and the limitations imposed by the wireless channel. Then it will be compared with the RSS counterpart focusing on the performance as a function of the channel behavior. What is introduced here is important to the understanding of the underlying issues in distance estimation, which is an important fundamental building block in WSN localization.TOA Based RangingIn TOA based ranging, a sensor node measures the distance to another node by estimating the signal propagation delay in free space, where radio signals travel at the constant speed of light. Figure 8.3 shows an example of TOA based ranging between two sensors. The performance of TOA based ranging depends on the availability of the direct path (DP) signal [4,14] . In its presence, for example, short distance line - of - sight (LOS) conditions, accurate estimates are feasible [14] . The challenge, however, is ranging in non - LOS (NLOS) conditions, which can be characterized as site - specific and dense multipath environments [14,22] . These environments introduce several challenges. The first corrupts the TOA estimatesdue to the multipath components (MPCs), which are delayed and attenuated replicas of the original signal, arriving and combining at the receiver shifting the estimate. The second is the propagation delay caused by the signal traveling through obstacles, which adds a positive bias to the TOA estimates. The third is the absence of the DP due to blockage, also known as undetected direct path (UDP) [14] . The bias imposed by this type of error is usually much larger than the first two and has a significant probability of occurrence due to cabinets, elevator shafts, or doors that are usually cluttering the indoor environment.In order to analyze the behavior of the TOA based ranging, it is best to resort to a popular model used to describe the wireless channel. In a typical indoor environment, the transmitted signal will be scattered and the receiver node will receive replicas of the original signal with different amplitudes, phases, and delays. At the receiver, the signals from all these paths combine and this phenomenon is known as multipath. In order to understand the impact of the channel on the TOA accuracy, we resort to a model typically used to characterize multipath arrivals. For multipath channels, the impulse respons 错误！未找到引用源。

无线红外传感器网络中英文对照外文翻译文献

中英文资料外文翻译文献外文资料AbstractWireless Sensor Network (WSN) has become a hot research topic recently. Great benefit can be gained through the deployment of the WSN over a wide range ofapplications, covering the domains of commercial, military as well as residential. In this project, we design a counting system which tracks people who pass through a detecting zone as well as the corresponding moving directions. Such a system can be deployed in traffic control, resource management, and human flow control. Our design is based on our self-made cost-effective Infrared Sensing Module board which co-operates with a WSN. The design of our system includes Infrared Sensing Module design, sensor clustering, node communication, system architecture and deployment. We conduct a series of experiments to evaluate the system performance which demonstrates the efficiency of our Moving Object Counting system.Keywords:Infrared radiation，Wireless Sensor Node1.1 Introduction to InfraredInfrared radiation is a part of the electromagnetic radiation with a wavelength lying between visible light and radio waves. Infrared have be widely used nowadaysincluding data communications, night vision, object tracking and so on. People commonly use infrared in data communication, since it is easily generated and only suffers little from electromagnetic interference. Take the TV remote control as an example, which can be found in everyone's home. The infrared remote control systems use infrared light-emitting diodes (LEDs) to send out an IR (infrared) signal when the button is pushed. A different pattern of pulses indicates the corresponding button being pushed. To allow the control of multiple appliances such as a TV, VCR, and cable box, without interference, systems generally have a preamble and an address to synchronize the receiver and identify the source and location of the infrared signal. To encode the data, systems generally vary the width of the pulses (pulse-width modulation) or the width of the spaces between the pulses (pulse space modulation). Another popular system, bi-phase encoding, uses signal transitions to convey information. Each pulse is actually a burst of IR at the carrier frequency.A 'high' means a burst of IR energy at the carrier frequency and a 'low'represents an absence of IR energy. There is no encoding standard. However, while a great many home entertainment devices use their own proprietary encoding schemes, some quasi-standards do exist. These include RC-5, RC-6, and REC-80. In addition, many manufacturers, such as NEC, have also established their own standards.Wireless Sensor Network (WSN) has become a hot research topic recently. Great benefit can be gained through the deployment of the WSN over a wide range ofapplications, covering the domains of commercial, military as well as residential. In this project, we design a counting system which tracks people who pass through a detecting zone as well as the corresponding moving directions. Such a system can be deployed in traffic control, resource management, and human flow control. Our design is based on our self-made cost-effective Infrared Sensing Module board which co-operates with a WSN. The design of our system includes Infrared Sensing Module design, sensor clustering, node communication, system architecture and deployment. We conduct a series of experiments to evaluate the system performance which demonstrates the efficiency of our Moving Object Counting system.1.2 Wireless sensor networkWireless sensor network (WSN) is a wireless network which consists of a vast number of autonomous sensor nodes using sensors tomonitor physical or environmental conditions, such as temperature, acoustics, vibration, pressure, motion or pollutants, at different locations. Each node in a sensor network is typically equipped with a wireless communications device, a small microcontroller, one or more sensors, and an energy source, usually a battery. The size of a single sensor node can be as large as a shoebox and can be as small as the size of a grain of dust, depending on different applications. The cost of sensor nodes is similarly variable, ranging from hundreds of dollars to a few cents, depending on the size of the sensor network and the complexity requirement of the individual sensor nodes. The size and cost are constrained by sensor nodes, therefore, have result in corresponding limitations on available inputs such as energy, memory, computational speed and bandwidth. The development of wireless sensor networks (WSN) was originally motivated by military applications such as battlefield surveillance. Due to the advancement in micro-electronic mechanical system technology (MEMS), embedded microprocessors, and wireless networking, the WSN can be benefited in many civilian application areas, including habitat monitoring, healthcare applications, and home automation.1.3 Types of Wireless Sensor NetworksWireless sensor network nodes are typically less complex than general-purpose operating systems both because of the specialrequirements of sensor network applications and the resource constraints in sensor network hardware platforms. The operating system does not need to include support for user interfaces. Furthermore, the resource constraints in terms of memory and memory mapping hardware support make mechanisms such as virtual memory either unnecessary or impossible to implement. TinyOS [TinyOS] is possibly the first operating system specifically designed for wireless sensor networks. Unlike most other operating systems, TinyOS is based on an event-driven programming model instead of multithreading. TinyOS programs are composed into event handlers and tasks with run to completion-semantics. When an external event occurs, such as an incoming data packet or a sensor reading, TinyOS calls the appropriate event handler to handle the event. The TinyOS system and programs are both written in a special programming language called nesC [nesC] which is an extension to the C programming language. NesC is designed to detect race conditions between tasks and event handlers. There are also operating systems that allow programming in C. Examples of such operating systems include Contiki [Contiki], and MANTIS. Contiki is designed to support loading modules over the network and supports run-time loading of standard ELF files. The Contiki kernel is event-driven, like TinyOS, but the system supports multithreading on a per-application basis. Unlike the event-driven Contiki kernel, the MANTIS kernel is based on preemptivemultithreading. With preemptive multithreading, applications do not need to explicitly yield the microprocessor to other processes.1.4 Introduction to Wireless Sensor NodeA sensor node, also known as a mote, is a node in a wireless sensor network that is capable of performing processing, gathering sensory information and communicating with other connected nodes in the network. Sensor node should be in small size, consuming extremely low energy, autonomous and operate unattended, and adaptive to the environment. As wireless sensor nodes are micro-electronic sensor device, they can only be equipped with a limited power source. The main components of a sensor node include sensors, microcontroller, transceiver, and power source. Sensors are hardware devices that can produce measurable response to a change in a physical condition such as light density and sound density. The continuous analog signal collected by the sensors is digitized by Analog-to-Digital converter. The digitized signal is then passed to controllers for further processing. Most of the theoretical work on WSNs considers Passive and Omni directional sensors. Passive and Omni directional sensors sense the data without actually manipulating the environment with active probing, while no notion of “direction” involved in these measurements. Commonly people deploy sensor for detecting heat (e.g. thermal sensor), light (e.g. infrared sensor), ultra sound (e.g. ultrasonic sensor), or electromagnetism (e.g. magneticsensor). In practice, a sensor node can equip with more than one sensor. Microcontroller performs tasks, processes data and controls the operations of other components in the sensor node. The sensor node is responsible for the signal processing upon the detection of the physical events as needed or on demand. It handles the interruption from the transceiver. In addition, it deals with the internal behavior, such as application-specific computation.The function of both transmitter and receiver are combined into a single device know as transceivers that are used in sensor nodes. Transceivers allow a sensor node to exchange information between the neighboring sensors and the sink node (a central receiver). The operational states of a transceiver are Transmit, Receive, Idle and Sleep. Power is stored either in the batteries or the capacitors. Batteries are the main source of power supply for the sensor nodes. Two types of batteries used are chargeable and non-rechargeable. They are also classified according to electrochemical material used for electrode such as NiCd(nickel-cadmium), NiZn(nickel-zinc), Nimh(nickel metal hydride), and Lithium-Ion. Current sensors are developed which are able to renew their energy from solar to vibration energy. Two major power saving policies used areDynamic Power Management (DPM) and Dynamic V oltage Scaling (DVS). DPM takes care of shutting down parts of sensor node which arenot currently used or active. DVS scheme varies the power levels depending on the non-deterministic workload. By varying the voltage along with the frequency, it is possible to obtain quadratic reduction in power consumption.1.5 ChallengesThe major challenges in the design and implementation of the wireless sensor network are mainly the energy limitation, hardware limitation and the area of coverage. Energy is the scarcest resource of WSN nodes, and it determines the lifetime of WSNs. WSNs are meant to be deployed in large numbers in various environments, including remote and hostile regions, with ad-hoc communications as key. For this reason, algorithms and protocols need to be lifetime maximization, robustness and fault tolerance and self-configuration. The challenge in hardware is to produce low cost and tiny sensor nodes. With respect to these objectives, current sensor nodes usually have limited computational capability and memory space. Consequently, the application software and algorithms in WSN should be well-optimized and condensed. In order to maximize the coverage area with a high stability and robustness of each signal node, multi-hop communication with low power consumption is preferred. Furthermore, to deal with the large network size, the designed protocol for a large scale WSN must be distributed.1.6 Research IssuesResearchers are interested in various areas of wireless sensor network, which include the design, implementation, and operation. These include hardware, software and middleware, which means primitives between the software and the hardware. As the WSNs are generally deployed in the resources-constrained environments with battery operated node, the researchers are mainly focus on the issues of energy optimization, coverage areas improvement, errors reduction, sensor network application, data security, sensor node mobility, and data packet routing algorithm among the sensors. In literature, a large group of researchers devoted a great amount of effort in the WSN. They focused in various areas, including physical property, sensor training, security through intelligent node cooperation, medium access, sensor coverage with random and deterministic placement, object locating and tracking, sensor location determination, addressing, energy efficient broadcasting and active scheduling, energy conserved routing, connectivity, data dissemination and gathering, sensor centric quality of routing, topology control and maintenance, etc.中文译文移动目标点数与红外传感器网络摘要无线传感器网络(WSN)已成为最近的一个研究热点。

Zigbee无线传感器网络英文文献与翻译

Zigbee Wireless Sensor Network in Environmental MonitoringApplicationsI. ZIGBEE TECHNOLOGYZigbee is a wireless standard based on IEEE802.15.4 that was developed to address the unique needs of most wireless sensing and control applications. Technology is low cost, low power, a low data rate, highly reliable, highly secure wireless networking protocol targeted towards automation and remote control applications. It’s depicts two key performance characteristics –wireless radio range and data transmission rate of the wireless spectrum. Comparing to other wireless networking protocols such as Bluetooth, Wi-Fi, UWB and so on, shows excellent transmission ability in lower transmission rate and highly capacity of network. A. Zigbee FrameworkFramework is made up of a set of blocks called layers.Each layer performs a specific set of services for the layer above. As shown in Fig.1. The IEEE 802.15.4 standard defines the two lower layers: the physical (PHY) layer and the medium access control (MAC) layer. The Alliance builds on this foundation by providing the network and security layer and the framework for the application layer.Fig.1 FrameworkThe IEEE 802.15.4 has two PHY layers that operate in two separate frequency ranges: 868/915 MHz and 2.4GHz. Moreover, MAC sub-layer controls access to the radio channel using a CSMA-CA mechanism. Its responsibilities may also include transmitting beacon frames, synchronization, and providing a reliable transmission mechanism.B. Zigbee’s TopologyThe network layer supports star, tree, and mesh topologies, as shown in Fig.2. In a star topology, the network is controlled by one single device called coordinator. The coordinator is responsible for initiating and maintaining the devices on the network. All other devices, knownas end devices, directly communicate with the coordinator. In mesh and tree topologies, the coordinator is responsible for starting the network and for choosing certain key network parameters, but the network may be extended through the use of routers. In tree networks, routers move data and control messages through the network using a hierarchical routing strategy. Mesh networks allow full peer-to-peer communication.Fig.2 Mesh topologiesFig.3 is a network model, it shows that supports both single-hop star topology constructed with one coordinator in the center and the end devices, and mesh topology. In the network, the intelligent nodes are composed by Full Function Device (FFD) and Reduced Function Device (RFD). Only the FFN defines the full functionality and can become a network coordinator. Coordinator manages the network, it is to say that coordinator can start a network and allow other devices to join or leave it. Moreover, it can provide binding and address-table services, and save messages until they can be delivered.Fig.3 Zigbee network modelII.THE GREENHOUSE ENVIRONMENTAL MONITORINGSYSTEM DESIGNTraditional agriculture only use machinery and equipment which isolating and no communicating ability. And farmers have to monitor crops’ growth by themselves. Even if some people use electrical devices, but most of them were restricted to simple communication between control computer and end devices like sensors instead of wire connection, which couldn’t be strictly defined as wireless sens or network. Therefore, by through using sensor networks and, agriculture could become more automation, more networking and smarter.In this project, we should deploy five kinds of sensors in the greenhouse basement. By through these deployed sensors, the parameters such as temperature in the greenhouse, soil temperature, dew point, humidity and light intensity can be detected real time. It is key to collect different parameters from all kinds of sensors. And in the greenhouse, monitoring the vegetables growing conditions is the top issue. Therefore, longer battery life and lower data rate and less complexity are very important. From the introduction about above, we know that meet the requirements for reliability, security, low costs and low power.A. System OverviewThe overview of Greenhouse environmental monitoring system, which is made up by one sink node (coordinator), many sensor nodes, workstation and database. Mote node and sensor node together composed of each collecting node. When sensors collect parameters real time, such as temperature in the greenhouse, soil temperature, dew point, humidity and light intensity, these data will be offered to A/D converter, then by through quantizing and encoding become the digital signal that is able to transmit by wireless sensor communicating node. Each wireless sensor communicating node has ability of transmitting, receiving function.In this WSN, sensor nodes deployed in the greenhouse, which can collect real time data and transmit data to sink node (Coordinator) by the way of multi-hop. Sink node complete the task of data analysis and data storage. Meanwhile, sink node is connected with GPRS/CDMA can provide remote control and data download service. In the monitoring and controlling room, by running greenhouse management software, the sink node can periodically receives the data from the wireless sensor nodes and displays them on monitors.B. Node Hardware DesignSensor nodes are the basic units of WSN. The hardware platform is made up sensor nodes closely related to the specific application requirements. Therefore, the most important work isthe nodes design which can perfect implement the function of detecting and transmission as a WSN node, and perform its technology characteristics. Fig.4 shows the universal structure of the WSN nodes. Power module provides the necessary energy for the sensor nodes. Data collection module is used to receive and convert signals of sensors. Data processing and control module’s functions are node device control, task sche duling, and energy computing and so on. Communication module is used to send data between nodes and frequency chosen and so on.Fig.4 Universal structure of the wsn nodesIn the data transfer unit, the module is embedded to match the MAC layer and the NET layer of the protocol. We choose CC2430 as the protocol chips, which integrated the CPU, RF transceiver, net protocol and the RAM together. CC2430 uses an 8 bit MCU (8051), and has 128KB programmable flash memory and 8KB RAM. It also includes A/D converter, some Timers, AES128 Coprocessor, Watchdog Timer, 32K crystal Sleep mode Timer, Power on Reset, Brown out Detection and 21 I/Os. Based on the chips, many modules for the protocol are provided. And the transfer unit could be easily designed based on the modules.As an example of a sensor end device integrated temperature, humidity and light, the design is shown in Fig. 5.Fig.5 The hardware design of a sensor nodeThe SHT11 is a single chip relative humidity and temperature multi sensor module comprising a calibrated digital output. It can test the soil temperature and humidity. The DS18B20 is a digital temperature sensor, which has 3 pins and data pin can link MSP430 directly. It can detect temperature in greenhouse. The TCS320 is a digital light sensor. SHT11, DS18B20 and TCS320 are both digital sensors with small size and low power consumption. Other sensor nodes can be obtained by changing the sensors.The sensor nodes are powered from onboard batteries and the coordinator also allows to be powered from an external power supply determined by a jumper.C. Node Software DesignThe application system consists of a coordinator and several end devices. The general structure of the code in each is the same, with an initialization followed by a main loop.The software flow of coordinator, upon the coordinator being started, the first action of the application is the initialization of the hardware, liquid crystal, stack and application variables and opening the interrupt. Then a network will be formatted. If this net has been formatted successfully, some network information, such as physical address, net ID, channel number will be shown on the LCD. Then program will step into application layer and monitor signal. If there is end device or router want to join in this net, LCD will shown this information, and show the physical address of applying node, and the coordinator will allocate a net address to this node. If the node has been joined in this network, the data transmitted by this node will be received by coordinator and shown in the LCD.The software flow of a sensor node, as each sensor node is switched on, it scans all channelsand, after seeing any beacons, checks that the coordinator is the one that it is looking for. It then performs a synchronization and association. Once association is complete, the sensor node enters a regular loop of reading its sensors and putting out a frame containing the sensor data. If sending successfully, end device will step into idle state; by contrast, it will collect data once again and send to coordinator until sending successfully.D. Greenhouse Monitoring Software DesignWe use VB language to build an interface for the test and this greenhouse sensor network software can be installed and launched on any Windows-based operating system. It has 4 dialog box selections: setting controlling conditions, setting Timer, setting relevant parameters and showing current status. By setting some parameters, it can perform the functions of communicating with port, data collection and data viewing。

传感器技术论文中英文对照资料外文翻译文献

传感器技术论文中英文对照资料外文翻译文献Development of New Sensor TechnologiesSensors are devices that can convert physical。

chemical。

logical quantities。

etc。

into electrical signals。

The output signals can take different forms。

such as voltage。

current。

frequency。

pulse。

etc。

and can meet the requirements of n n。

processing。

recording。

display。

and control。

They are indispensable components in automatic n systems and automatic control systems。

If computers are compared to brains。

then sensors are like the five senses。

Sensors can correctly sense the measured quantity and convert it into a corresponding output。

playing a decisive role in the quality of the system。

The higher the degree of n。

the higher the requirements for sensors。

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the n industry includes three parts: sensing technology。

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and computer technology。

车载无线传感器网络监测系统设计(外文原文+中文翻译)

Wireless sensor network monitoring system designKang yi-mei,Zhao lei,Hu jiang,Yang en-bo(Study on Beijing University of Aeronautics and Astronautics)Summary: A car wireless sensor network monitoring system based on IEEE 802.15.4 and ZigBee standards. With universal wireless sensor networks, expansion of the scope of monitoring and monitoring functions for in-car system, car data acquisition and condition monitoring of equipment status and the necessary equipment control, topology control, topology query functions. Keywords: wireless sensor networks; monitoring systemIntroductionIn order to satisfy the people to car safety, handling and comfort requirements, vehicle integrated with more and more electronic system .At present, car electronic equipment is widely used 16 or 32-bit microprocessor control. Creating in-vehicle monitoring system based on IEEE 802.15.4 and ZigBee standard for wireless sensor networks, designed to achieve a more optimized wireless sensor networks, the progressive realization of the network of automotive systems, intelligent and controllable to provide high-Car System security.System designIn this paper, the existing vehicle system, the data transmission mode is extended to the wireless transmission mode, the realization of a star network data acquisition system. And can place each data acquisition node of the acquired data is transmitted to the gateway, the gateway through the serial port to upload data to the host computer, in the host data real-time waveform display, and method of database to preserve, for the follow-up data processing. The application of system object is composed of a temperature sensor, pressure sensor, speed sensor, speed sensor, a current sensor, pressure sensor, sensor subsystem. The purpose of this design is to use a monitoring host machine end to the detection of multiple target environment, taking into account the access data throughput and software system complexity, using time-division multiplexing way, one by one on the net terminal collecting point of control and data acquisition.As shown in Figure 1, the system is divided into 3 parts: Vehicle Monitoring Center, gateway and mobile sensor node. Gateway is the whole vehicle system core, and all vehicular sensor node communication. Vehicle monitoring center to the gateway sends a control command by the gateway, the control command is converted to an RF signal and sent to the vehicle sensor node. When the vehicle sensor nodes to transmit data, gateway into the data reception state, and upload data to the monitoring center for further processing. In addition, car between sensor nodes cannot communicate with each other. The monitoring center of the monitoring software and gateway in RS232standard interface for communication.Vehicle sensor node life cycle is active and dormant periods. Nodes in the active phase of the completion of data acquisition, data sent to the gateway, receiving andexecuting gateway command; in the dormant period off the wireless RF module in order to save energy, until the next active period. System through this mechanism of dormancy to reduce energy consumption, extend the time span of the system as a whole.The system used PC as the control center, PC machine monitoring software in VB development environment, is a dialog based application software. In order to improve the communication module of the intelligent level, in the design, its function is not limited to the real-time data display, all of the data collection by the monitoring software by sending a request signal to the trigger. Considering the original data for subsequent processing and in-depth analysis of the vehicle system, can accurately judge, software has also added data preservation of the document and data file display function.Generally speaking, the whole network are controlled by the host monitoring software, the working process of every node of the network is the need of human participation.2 hardware system design2.1application chip introductionMC13192with IEEE802.15.4 standard, the operating frequency is2.405～2.480 GHz, data transmission rate of 250kbps, using 0-QPSK debugging mode. This feature-rich two-way 2.4GHz transceiver with a data modem which can be in the ZigBee technology application. It also has an optimized digital core, helps to reduce the MCU processing power, shorten the cycle of execution.The main control MCU choose HCS08series of low power, high performance microprocessor MC9S08GB60. The processor has a 60Application of KB programmable Flash、4 KB RAM,10 ADC,8 channel2 asynchronous serial communication interface ( SCI ),1 synchronous serial interface ( SPI ) and I2C bus module, can fully meet the requirement of vehicle gateway and node processor requirements.2.2 MCl3192and MC9S08GB60hardware connectionMC13192and MC9S08GB60 hardware connection diagram as shown in figure 2. The MC13192control and data transmission on 4 wire serial peripheral interface ( SPI ) is completed, the4interface signals were MOS-I, MISO,, SPICLK. The main control MCU through the control signal exiting sleep mode or hibernation mode, through to reset the transceiver, through the RXTXEN to control the data sending and receiving, or force the transceiver into idle mode. The sensor output analog signal through MCU 8 Channel10 bit ADC conversion input to MCU. MCU via SPI MC13192to read and write operation, and the sensor to collect the signal processed by MC13192launch out. The MC13192 interrupt IRQ interrupt register through the pins and to judge the type of interrupt. MC908GB60 pin to control the MC13192 into a different mode of operation .Control of the sensor signal from the MC13192receiving antenna in, transmitted via SPI to MCU, after MCU judgment after processingthrough the GPIO port is transmitted to the sensor, complete control of the sensor. At the same time, MCU MC13192transceiver control and the MAC layer operation. The 3system software design3.1of overall software designThe software design is the design of the core, the key lies in the overall framework of software and data structure design. An important factor to consider is a efficiency, another is to design the clarity.System software consists of the gateway node and the sensor node is composed of two parts, the two parts are needed to complete the SMAC protocol transplantation, and according to the different needs for the upper communication applications with API interface function. Because the SMAC protocol stack programming model using hierarchical design, only the underlying PHY and MAC program level and related hardware, and network layer and application layer procedures is not affected by hardware effects. SMAC in different hardware platform transplantation only need to modify the PHY and MAC layer, each layer can shield the hardware differences directly run.As shown in Figure 3, the design of the software for system platform layer, protocol layer and application layer 3layer. At the same time, defines 3API interface: system layer interface, protocol layer and application layer interface. System level interface defines a hardware register mapping, so C language to be able to directly access the hardware registers to control hardware. System platform based on real-time operating system μC/II protocol layer, to provide system services Hardware driving module provides the hardware driver, all of the hardware control through the module to provide services. Platform layer protocol layer interface protocol layer to provide services. Protocol layer is based on the IEEE 802.15.4 physical layer and link layer based on the ZigBee network layer protocol. Application layer through the application layer interface to invoke services provided by the protocol layer, network management and data transfer tasks. Application of configuration module can call protocol layer to provide network services, will direct the system configuration and query, it is mainly through the AT commands to achieve, so the module calls the application layer interface and protocol layer interface to provide services.3.2sensor node software designBased on the long-term use of the functional requirements, sensor nodes in the software design is the key to achieve the required functions, and can minimize the energy consumption of the sensor nodes.It was found, ZigBee module and the energy consumption is much larger than the central processor and the energy consumption of sensor module. Therefore, the sensor node design of application software to try to make each module in a dormant state, and minimizing wakes ZigBee module number. Therefore, the sensor nodes, power of each functional module initialization is completed, and joined the network, enter the Sleep state, the central processor cycles to be timed wake-up to send data tothe gateway, and receives the gateway command. Sensor nodes of the workflow are shown in Figure 4.The 3.3 gateway node software designGateway downward management sensor node, to complete and PC monitoring center of interaction, the need for a complicated task management and scheduling, therefore, based on the uC / OS kernel of embedded operating system to manage the gateway, the application task efficiently provide good software support. According to gateway function demand, the μC / OS-II, SMAC protocol organic union, form a network operating environment, the user can conveniently on the basis of its development and application. Based on μC / OS-II extended gateway software platform structure is shown in figure 5. Based on μC / OS-II operating system, were used to build the system task SYS_task ( ), START_task ( SMAC star network task ), gateway and a sensor node interaction task COMM_task ( ), PC monitoring center port monitoring mission ( SER_task ) applications such as a series of tasks, thus realizing the gateway software application function.The 3.4 host monitoring software designThis system is the ultimate goal of the collected vehicle sensor data is transmitted in real-time to the host, and the host of display and preservation. Display is designed to get on-board sensor node monitoring environment of the initial situation, preservation is designed as an in-depth analysis of the data samples. In addition, the system as a whole the main prosecution and the data acquisition request initiator, need to be able to send the data request signal in accordance with the requirements of. According to the above requirements, VB environment in the development of a dialog based application. This application includes a 4 module:①data waveform display module. The role of the module is a form of waveform data of the node to be displayed in real-time, it is the use of MS Chart and Timer control.②topology display module. When the user wants to know the wireless sensor network topology construction situation, you can view the topological information, understanding of network nodes join and loss.The historical data display module. In vehicle network system to a certain period of the past, may need a certain period of time the original data for subsequent processing and in-depth analysis, so that the vehicle system of accurate judgement. With the aid of historical data display module, the control center from the gateway of the data obtained, according to the different attributes of the nodes, address and time are saved to the database of the corresponding field, and may be will displayed by waveform of historical data, for the user analysis.The controlling module :In vehicle during system operation may be concerned about a vehicle sensor value node, or to a sensor threshold settings, for monitoring environmental exceptions can be promptly reported to the system. These are available through the control module of the system are corresponding to the set, the control module can also be on the system in which one does not need to delete the node.In short, through the host monitoring software users can visually and many aspects ofgeneral wireless sensor network systems to understand and use.4 test and verification4.1 testingTesting equipment:4 MCl3192ZigBee chip node,1as a gateway node, the remaining 3as sensor nodes.Test method: the gateway node power,4 LED and light, scanning channel if the search to the idle channel, the LED goes out and join the free channel for. The sensor node power,4 LED scanning in the channel at the same time, polling light. LED1 flashes once when the sensor nodes receive the allocation address of the gateway node, So far, networking process and address binding process is complete.4.2 Zigbee RF communication testTesting equipment: ZigBee node 4, a computer terminal stationTest method: according to the ZigBee transmission frame format, the actual transmission total bytes for ( n 6), namely ( n 6) bytes for a data packet. According to the set parameters of the software, such as packet loss is the loss number plus 1. If the received data packet, receives the data packet number plus 1, and then sends the data were compared with data, if the data is correct, the number of packets plus 1, and error packets number plus 1. The last statistic results, can know the data packet loss and packet error rate. The 4 node to form a ZigBee network,1 of them as the gateway, the remaining 3 nodes for sensor node. Write a program to set:3nodes and gateway communications, computer terminal and the gateway is connected through RS232, terminal equipment software records from the 3node to receive data, nodes work at 2.4 GHz frequencies, transmission of a byte of data, circular send 100 times. To obtain the final3 node test average as a result of the data analysis. Star network radio frequency communication BER test results as shown in table 1.Experimental analysis of: in a star network for data transmission, the test results significantly worse on a single point to single point transmission mode. This is mainly because, in the transmission process node must exist between the frequency interference and other interference.4.3power testSystem status and hibernation, respectively, using a multimeter to test the gateway node and the power consumption of sensor nodes, the test results listed in Table 2.ConclusionThis paper analyzes the IEEE 802.15.4 and ZigBee protocol, combined with the general development principles of communication systems and embedded systems, IEEE802.15.4 protocol on the μC / OS-II operating system, select the appropriate hardware and software platform, focusing on software support for the platform, the software design of the overall structure of the communication protocol stack, andultimately to achieve a compliant with the ZigBee specification car star wireless data acquisition network. The system has the following advantages:①system easy to install. Wireless interconnection makes the equipment installation location is flexible to meet the requirements of the automation system is installed. It is simply that the power can take equipment. The network system can automatically complete the network configuration.②scalability. Equipment within the coverage of the vehicle gateway, turn on the device, the node will automatically join the network.③network self-healing ability. If the network is a device fails, the vehicle gateway can automatically monitor, issue the command the device reset and re-network.车载无线传感器网络监测系统设计康一梅，赵磊，胡江，杨恩博（就读于北京航天航空大学）摘要：基于IEEE 802．15．4和ZigBee标准实现了一个车载无线传感器网络监测系统。

无线传感器网络英文摘要与翻译

AbstractA1（1）In the recent years, as the rapid development of MEMS, wireless communication network, embedded system, and the interaction of all kinds of new technologies, many new modes of information obtaining and process come into being. A2（2）Wireless sensor network (WSN) is one of them. A2（3）WSN can be used to monitor the environments, the machines and even the people; hence “ubiquitous computing” will come true. A2（4）WSN has wide application fields, so it has been paid high attention by the military, the academes, and the industrial from all over the world. A2（5）Meanwhile, this provides many challenges in the academe foundations and technologies.A3（6）This dissertation introduces the recent researches on WSN, and analyzes its key technologies：the setup of wireless communication network, the design and implementation of network nodes and the design steps of WSN, in an architecture view.A4（7）By analyzing and comparing, ZigBee technology is adopted to setup wireless communication network. A4（8）The topology of the network and hierarchical protocol stacks are designed. A4（9）The embedded network nodes are designed and developed, and the hardware and software are implemented. A4（10）An experimental WSN is deployed and the experimental data is collected and analyzed. A5（11）Finally, a typical example of wireless sensor network, personnelidentification and positioning system in mine, is presented. Keywords: Wireless sensor network, Embedded systems, IEEE802.15.4 protocols, ZigBee摘要近年来，随着微机电系统(MEMS)、无线通信网络和嵌入式系统等技术的飞速发展，各种新技术的融合，出现了许多信息获取和处理的新模式，无线传感器网络就是其中一例。

无线传感器网络应用文章英文

无线传感器网络应用文章(英文) Wireless Sensor Network ApplicationsIntroduction:Wireless Sensor Networks (WSNs) have gained significant attention in recent years due to their potential for numerous applications in various fields. A WSN consists of a large number of small, low-cost sensor nodes that are wirelessly connected to monitor physical or environmental conditions. These nodes can collect, process, and transmit data to a central base station for further analysis. This article aims to explore some of the most promising applications of WSNs.Environmental Monitoring:One of the most common applications of WSNs is environmental monitoring. These networks can be deployed in remote or hazardous areas to monitor parameters such as temperature, humidity, air pollution, and water quality. For instance, in forest fire detection, sensor nodes can detect abnormal temperature increases and transmit an alert to authorities, enabling timely intervention. In agriculture, WSNs can monitor soil moisture levels and provide farmers with real-time data to optimize irrigation.Healthcare:WSNs have also found applications in the healthcare industry. They can be used to monitor vital signs of patients, such as heart rate, blood pressure, and body temperature. Sensor nodes attached to patients can wirelessly transmit data to healthcare professionals, enabling continuous monitoring and early detection of any abnormalities. WSNs areparticularly useful in remote patient monitoring, allowing patients to receive medical attention from the comfort of their homes.Smart Homes and Buildings:WSNs can play a crucial role in creating smart homes and buildings. By deploying sensor nodes throughout a building, various parameters such as temperature, lighting, occupancy, and energy consumption can be monitored and controlled. This enables energy-efficient operations by optimizing heating, cooling, and lighting systems based on real-time data. Additionally, WSNs can enhance security by detecting unauthorized access or unusual activities within a building.Industrial Automation:WSNs are widely used in industrial automation to monitor and control different processes. For example, in manufacturing plants, sensor nodes can collect data on machine performance, temperature, and vibration levels, allowing for preventive maintenance and reducing downtime. WSNs can also be used for inventory management, tracking the movement of goods within a warehouse, and ensuring timely restocking.Traffic Management:WSNs can significantly contribute to improving traffic management in urban areas. By deploying sensor nodes along roads, real-time traffic data, such as vehicle density and speed, can be collected. This information can be used to optimize traffic signal timings, detect congestion, and provide drivers with alternative routes, reducingoverall travel time and fuel consumption. WSNs also enable the implementation of intelligent transportation systems, enhancing safety and reducing accidents.Conclusion:Wireless Sensor Networks have found numerous applications in various fields, ranging from environmental monitoring to healthcare, smart homes, industrial automation, and traffic management. These networks offer a cost-effective and scalable solution for collecting and analyzing datain real-time. As technology continues to advance, it is expected thatthe applications of WSNs will continue to expand, revolutionizing different industries and improving the quality of life for people around the world.。

无线传感中英文对照外文翻译文献

(文档含英文原文和中文翻译)中英文对照翻译译文:无线传感器网络的实现及在农业上的应用1引言无线传感器网络（Wireless Sensor Network ,WSN）就是由部署在监测区域内大量的廉价微型传感器节点组成，通过无线通信方式形成的一个多跳的自组织的网络系统。

其目的是协作地感知、采集和处理网络覆盖区域中感知对象的信息，并发送给观察者。

“传感器、感知对象和观察者”构成了网络的三个要素。

这里说的传感器，并不是传统意义上的单纯的对物理信号进行感知并转化为数字信号的传感器，它是将传感器模块、数据处理模块和无线通信模块集成在一块很小的物理单元，即传感器节点上，功能比传统的传感器增强了许多，不仅能够对环境信息进行感知，而且具有数据处理及无线通信的功能。

借助传感器节点中内置的形式多样的传感器件，可以测量所在环境中的热、红外、声纳、雷达和地震波信号等信号，从而探测包括温度、湿度、噪声、光强度、压力、土壤成分、移动物体的大小、速度和方向等等众多我们感兴趣的物质现象。

无线传感器网络是一种全新的信息获取和信息处理模式。

由于我国水资源已处于相当紧缺的程度,加上全国90%的废、污水未经处理或处理未达标就直接排放的水污染,11%的河流水质低于农田供水标准。

水是农业的命脉,是生态环境的控制性要素,同时又是战略性的经济资源,因此采用水泵抽取地下水灌溉农田,实现水资源合理利用,发展节水供水,改善生态环境,是我国目前精确农业的关键，因此采用节水和节能的灌水方法是当今世界供水技术发展的总趋势。

2无线传感器网络概述2.1无线传感器网络的系统架构无线传感器网络的系统架构如图1所示，通常包括传感器节点、汇聚节点和管理节点。

传感器节点密布于观测区域，以自组织的方式构成网络。

传感器节点对所采集信息进行处理后，以多跳中继方式将信息传输到汇聚节点。

然后经由互联网或移动通信网络等途径到达管理节点。

终端用户可以通过管理节点对无线传感器网络进行管理和配置、发布监测任务或收集回传数据。

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(文档含英文原文和中文翻译)中英文对照翻译基于网络共享的无线传感网络设计摘要：无线传感器网络是近年来的一种新兴发展技术，它在环境监测、农业和公众健康等方面有着广泛的应用。

在发展中国家，无线传感器网络技术是一种常用的技术模型。

由于无线传感网络的在线监测和高效率的网络传送，使其具有很大的发展前景，然而无线传感网络的发展仍然面临着很大的挑战。

其主要挑战包括传感器的可携性、快速性。

我们首先讨论了传感器网络的可行性然后描述在解决各种技术性挑战时传感器应产生的便携性。

我们还讨论了关于孟加拉国和加利尼亚州基于无线传感网络的水质的开发和监测。

关键词：无线传感网络、在线监测1.简介无线传感器网络，是计算机设备和传感器之间的桥梁，在公共卫生、环境和农业等领域发挥着巨大的作用。

一个单一的设备应该有一个处理器，一个无线电和多个传感器。

当这些设备在一个领域部署时，传感装置测量这一领域的特殊环境。

然后将监测到的数据通过无线电进行传输，再由计算机进行数据分析。

这样，无线传感器网络可以对环境中各种变化进行详细的观察。

无线传感器网络是能够测量各种现象如在水中的污染物含量，水灌溉流量。

比如，最近发生的污染涌流进中国松花江，而松花江又是饮用水的主要来源。

通过测定水流量和速度，通过传感器对江水进行实时监测，就能够确定污染桶的数量和流动方向。

不幸的是，人们只是在资源相对丰富这个条件下做文章，无线传感器网络的潜力在很大程度上仍未开发，费用对无线传感器网络是几个主要障碍之一，阻止了其更广阔的发展前景。

许多无线传感器网络组件正在趋于便宜化（例如有关计算能力的组件），而传感器本身仍是最昂贵的。

正如在在文献[5]中所指出的，成功的技术依赖于共享技术的原因是个人设备的大量花费。

然而，大多数传感器网络研究是基于一个单一的拥有长期部署的用户，模式不利于分享。

该技术管理的复杂性是另一个障碍。

大多数传感器的应用，有利于这样的共享模型。

我们立足本声明认为传感器可能不需要在一个长时间单一位置的原因包括：（1）一些现象可能出现变化速度缓慢，因此小批量传感器可进行可移动部署，通过测量信号，充分捕捉物理现象（2）可能是过于密集，因此多余的传感器可被删除。

（3）部署时间短。

我们将会在第三节更详细的讨论。

上述所有假定的有关传感器都可以进行部署和再部署。

然而有很多的无线传感器网络由于其实时监测和快速的网络功能可能被利用作为共享资源。

其作为共同部署资源要求，需要一些高效的技术，包括对传感器的一些挑战，如便携性，流动频繁的传感器内的部署，这使我们在第四节将会有大的挑战。

在本文中，我们专注于作为共享的可行性设计的传感器网络。

下面我们开始阐述传感网络在孟加拉国和加利福尼亚州的水质检测中的应用。

2．无线传感网络在水质监测中的应用无线传感器网络是通过把小型计算机设备连接到各式传感器和无线电而组成的。

这些设备自适应的形成特殊网络（暂时的点对点网络），通过无线方式对所处环境进行监测、处理。

其硬件和软件的设计非常低功耗以此达到长期在现场部署的目的，即此种部署在所处环境中人为干预性小。

设备大小通常从四分之一个个人数据处理机到类似一个个人数据处理机的装置那么大。

在一般情况下，资源可用性和功耗与设备大小是相一致的。

例如，虽然资源可用性在很大程度上取决于传感器的功耗，但是低功率节点（通常称为微尘）用两节AA电池可以运行大约一二个月。

传感器网络提供密集的空间和时间上的采样。

此种取样即使是在偏远和难以到达的地方均可采样。

因此，它是对于在时间上和空间上要求精确采集最适用的网络技术。

例如无线传感网络在土壤中的应用就是个很好的例子。

因为土壤环境在空间上是多样性的，需要精确的时间上的采样。

对于突然发生的变化都会被精确的采样及时记录下来。

事实上，无线传感器网络是一种低功耗的网络技术，对于一些发达地区其作为一种新兴技术适用性更为广泛。

此外，对于公共健康方面的应用极为重要。

例如，参考文献（17）阐述了人们对于水质的极高的关注度，“对水质的分析起初仍然是通过实验采样的办法将采集到的样本带回实验室进行研究。

”这种类型的数据收集和分析通常是非常耗时的且大多是不准确的，并在许多情况下，错过了人们对于及时关注的焦点的分析。

我们参与了两项正在进行的关于地下水质监测的无线传感网络部署：一项系统是以了解孟加拉国地下水中砷的含量为主。

另一项系统是通过研究孟加拉国地下水和土壤来监测硝酸盐的传播。

以上我们的部署都具有类似的设置。

一个塔架，是由外围箱体式的无线设备组成，这些设备在土壤中通过长导线连接到嵌入式传感器。

每个设备可以支持7个传感器，每个塔架都有多个设备。

多路塔架被部署在目的地周围，以达到空间上垂直和水平的密集部署。

这些设备将采集到的样本以无线方式传送给基站以供分析。

该部署的基站是一个个人数据处理机类的设备，也可以是一种轻便电脑。

它是通过由太阳能提供再充电的汽车电池来进行供电。

为了能够获得外部数据，我们的基站使用Zigbee技术，或在Zigbee不可用时，使用GPRS网络。

在孟加拉国，在恒河三角洲的几千万人饮用了已被砷严重污染的地下水，如果被污染的水量一直持续，由砷引起的患病率和皮肤癌将大约每年分别增加两百万和一万例，由砷引起的癌症的死亡率每年将会大约增加三千例。

我们对于控制砷在地下水中的动态变化是难以完全了解的。

在与孟加拉国的工程技术大学和麻省理工学院进行合作中，我们于2006年1月在靠近达卡的一个水稻地里部署了一个传感网络，目的是为了帮助确认这个假说成立。

一个完整的塔架应该包含3部分完整的传感器（土壤湿度，温度，碳酸盐，钙，硝酸，氯，氧化还原电位，氨氮，pH值），每个部署都具有不同的深度（在地面以下1，1.5，2米），在此基础上的压力传感器用来监测水的深度。

在干旱地区和半干旱地区水的短缺和不断增加的对于水资源的消耗已经促进人们重新再利用被处理过的废水。

尽管对于水资源的再利用人类收获了很多益处，但是已被处理的废水对于人类的健康和环境质量仍然存在着显而易见的危害。

解决这些危害需要进行自动的分布式的观测和控制灌溉水量，查出它所传输的污染物，包括暂停处理的或是还未处理的污染物，胶状污染物，药物，有机碳，挥发性有机化合物，治病微生物，营养素例如氮或磷。

在加利福尼亚的帕姆代尔，一个水质再利用现场是为测试土壤湿度，温度和硝酸盐的传感器网络而被用作的试车台。

此网络集合了两个方面：第一，确保此环境正在被监测，第二，提供对水质控制的反馈，从而达到优化水流量和减少化学物质渗透到地下。

这种现场也可以被用来在对孟加拉国进行部署前对软件，传感器和硬件的测试。

3．传感器共享技术对于传感器网络数据收集，即使是最小的传感器资源，其共享也将让许多人受益。

我们相信以下三种技术方法特别适用于传感器共享：（1）从一系列小型传感器大范围部署到精确仿真。

（2）从密集部署到稀疏部署逐渐移动冗余传感器（3）在一些可能的地区缩短部署周期。

在这里，我们更详细地描述这些场景，包括我们自己和别人在执行有关的或支持的算法时的工作的调查。

(1)精确仿真人类功能的移动性就是通过手动来模拟一个使用较少传感器的密集部署区。

人们可以移动一个领域的一小套传感器，对密集空间收集数据。

该技术将是只适合于可持续发展应用中，所关注的现象变化非常缓慢。

(2)密集到稀疏部署一些传感器网络应用需要一个密集映射的环境。

一旦传感器密集部署和细节的现象揭示，我们可以看到它可以捕获足够的资料较少的传感器，从而释放传感器部署在其他地方。

这里，我们描述适用的工作是正在进行中的传感器网络社区。

(3)部署周期短有些应用程序只需要短时间部署，因而对传感器的共享是种理想选择。

我们在孟加拉的部署是一个带有部署周期短的应用例子。

我们要收集数据，以验证有关昼夜变化的假设，所以我们希望数天时间来对数据进行分析。

4．挑战许多挑战性技术的出现，是为了能够快速部署和移动传感器，主要因为迄今为止的工作主要集中在静态的，长期运行的部署中。

我们已经有了趋于密集化的目标，降低高密度部署使之稀疏，使周期短的部署趋于平衡，我们发现以下三个挑战是最恰当的。

算法必须是具有人机通信功能的，对于人为错误是可以解决的。

对于系统故障必须迅速查明，并最大限度地通过正确的数据进行接收。

最后，系统必须迅速做出部署。

5．结论无线传感器网络可视为一种工具，其对于可持续发展来说具有很好的潜力。

如果我们视这种发展的无线传感网络技术为共享资源的话，它就可以得到技术社区的帮助。

为了使无线传感器网络作为一种共享资源得到落实，我们确定了三个有希望的技术方法：精确仿真，从密集部署到稀疏部署，实施短周期部署。

我们讨论了我们的工作部署，这些部署已证明了这些技术，描述了我们的过去和现在需要做哪些工作去面对即将出现的重大挑战。

Designing Wireless Sensor Networks as aShared Resourcefor Sustainable DevelopmentAbstract ：Wireless sensor networks (WSNs) are a relatively new and rapidly developing technology; they have a wide range of applications including environmental monitoring, agriculture, and public health. Shared technology is a common usa ge model for technology adoption in developing countries. WSNs have great potential to be utilized as a shared resource due to their on-board processing and ad-hoc networking capabilities, however their deployment as a shared resource requires that the technical community ﬁrst address several challenges. The main challenges include enabling sensor portability–the frequent movement of sensors within and between deployments, and rapidly deployable systems–systems that are quick and simple to deploy.We ﬁrst discuss the feasibility of using sensor net-works as a shared resource, and then describe our research in addressing the various technical challenges that arise in enabling such senso rportability and rapid deployment. We also outline our experiences in developing and deploying water quality monitoring wireless sensor networks in Bangladesh and California.Key words: WSNs、on-board processing1 IntroductionWireless Sensor Networks (WSNs), networks of wirelessly connected sensing and computational devices, hold tremendous promise for many areas of development including public health,the environment, and agriculture. A single device has a processor, a radio, and several sensors. When a network of these devices is deployed in a ﬁeld, the sensing devices measure particular aspects of the environment. The devices then communicate those measurements by radio to one another and to more powerful computers for data analysis. In this way, WSNscan provide detailed observations of various phenomena that occur in the environment.WSNs are capable of measuring diverse phenomena such as contaminant levels in water, pollutants in the air, and the ﬂow of water for irrigation. As an example of a potential application, consider the recent incident of contamination spilling into the Songhua river in China, the main source of drinking water for many people1. Determining rate of ﬂow and sometimes direction of the river requires coordination of multiple sampling points. Sensors periodically taking samples at multiple locations along the river could determine the rate, quantity, and direction of contaminant ﬂow using the distributed sensing and processing of a wireless sensor network.Unfortunately, the potential of wireless sensor net-works for sustainable development2 remains largely untapped while they are designed primarily for relatively resource-rich application contexts. The cost of WSNs is one of several major barriers that prevents them from being leveraged for sustainable development applications. Many components of WSNs are becoming cheaper (e.g. computing power), but the sensors themselves remain the most expensive component3. As stated in [5], successful technology-based international development projects rely on shared technology due to excessive cost of personal devices. However, most research on sensor networks is based on long-term deployments owned by a single user, a paradigm not conducive for sharing. The complexity of technology management is another barrier. We use Grameen telecom as a successful model 4 in which the management and maintenance of shared hardware is centralized. We envision a sensor network much in the same light.Many sensor network applications are conducive to such a shared model. We base this statement on the observation that sensors may not be required in a single location for extended periods of time for reasons including: (1) a phenomenon of interest may have a slow rate of change, thus a small number of sensors can bemoved within a deployment, emulating the density required to suciently capture the physical phenomena, (2) the initial deployment may have been too dense, thus redundant sensors can be removed, and (3) the duration of the deployment may be short. We discuss these scenarios in more detail in Section 3.All of the deployment scenarios mentioned above rest on the assumption that sensors can be easily deployed and re-deployed. While WSNs have great potential to be utilized as a shared resource due to their on-board processing and ad-hoc networking capabilities, their deployment as a shared resource requires that the technical community ﬁrst address several challenges, including enabling sensor portability – the frequent movement of sensors within and between deployments, and rapidly deployable systems – systems that are quick and simple to deploy. This leads us to our major challenges in Section 4.Clearly, the primary issues related to successful technology adoption are the social, policy, and logistical questions to be answered in order to enable equitable access and the design of culturally appropriate technology. Our experience, though relevant, is limited to our technical expertise. These challenges and others should be formulated more explicitly with the necessary diverse input from communities, activists, governments and NGOs.In this paper we focus on justifying the technical feasibility of designing sensor networks as a shared technology (Section 3) and describing the technical challenges that must be addressed to enable WSNs as a shared technology (Section 4). We begin by describing our applications in water quality monitoring in Bangladesh and California (Section 2).2 WSNs For Water QualityWireless sensor networks are made up of small computational devices connected to various sensors and wireless radios. The devices automatically and adaptively form ad-hoc networks (temporary point-to-point networks) over wireless radios to make decisions based on measurements of their environment. Thehardware and software are designed to be extremely low power in order to enable long-term in-situ deployments, i.e. undisturbed deployments that are left in the environment with minimal human intervention. Device sizes commonly range from that of a quarter to a PDA-like device. In general, resource availability and power consumption are commensurate with size. For example, while it largely depends on the power consumption of the sensors, the lower-power nodes (often called motes) can run for approximately one month on 2 AA batteries.Sensor networks provide dense spatial and temporal sampling even in remote and hard to reach locations. Thus, they are best applied to applications that need dense sampling in space and/or time. Soi applications are a good example, because the soi environment is heterogeneous across space, requiring dense spatial sampling. Abrupt changes can then be captured with a high temporal sampling rate.The fact that WSNs are low power and wireless makes them appealing as a technology for developing regions, but in addition the dense sampling is crucial for public health applications. For example, [17] states that while water quality concerns can be extremely critical, “analysis is still primarily conducted in a laborious manner by physical collection of a sample that is analyzed back in a laboratory.” This kind of data collection and analysis is time consuming and mostly undirected, and in many instances misses the toxin events of interest.We are involved with two ongoing WSN deployments related to groundwater quality: a system to understand the prevalence of arsenic in Bangladesh groundwater, and a system to monitor nitrate propagation through soils and ground water in California.Both of our deployments have a similar setup. A pylon [10] (Figure 2) consists of an enclosure housing the small wireless devices which connect to groups of sensors embedded at multiple depths in the soil through long wires. Each devicecan support 7 sensors and there are multiple devices per pylon. Multiple pylons are deployed around the ﬁeld to attain vertical and horizontal spatial density. The devices wirelessly transmit samples back to a base-station for analysis (Figure 1). The base-station in these deployments was a PDA-class device. It could also be a laptop. It is powered by a car-battery recharged using solar panels. To make data externally accessible, our base-station is connected using Zigbee or where Zigbee is unavailable, using a GPRS (i.e. cellular) network.In Bangladesh, tens of millions of people in the Ganges Delta drink ground water that is dangerously contaminated with arsenic. If consumption of contaminated water continues, the prevalence of arsenicosis and skin cancer will be approximately 2,000,000 and 100,000 cases per year, respectively, and the incidence of death from cancer induced by arsenic will be approximately 3,000 cases per year [18].A full understanding of the factors controlling arsenic mobilization to ground water is lacking. In a joint collaboration with scientists at the Bangladesh University of Engineering and Technology and MIT, we deployed a sensor network in January of 2006 in a rice ﬁeld near Dhaka,Bangladesh in order to aid in validating this hypothesis. A full pylon contains 3 complete suites of sensors (soil moisture, temperature, carbonate, calcium, nitrate, chloride, oxidation-reduction potential, ammonium, and pH), each deployed at a diﬀerent depth (1, 1.5, and 2 meters below ground), and a pressure transducer at the base to monitor water depth.Water scarcity in arid and semi-arid regions and increasing demand on water supplies has stimulated interest in the reuse of treated wastewater. Despite the many beneﬁts to irrigating with reclaimed water,there remain both real and perceived risks to human health and environmental quality stemming from residuals in the treated wastewater. Proactively addressing these risks requires automating the distributed observation and control of the irrigation water and thetrace pollutants that it conveys, including suspended or dissolved solids (TDS), colloidal solids, pharmaceuticals, organic carbon, volatile organic compounds, pathogenic microorganisms, and nutrients such as nitrogen or phosphorus. A water reuse site in Palmdale, California is being used as a testbed for a sensor network with soil moisture, temperature, and nitrate sensors. The network focuses on two things: ﬁrst,ensuring that environmental regulations are being met, and second, providing feedback to a water control system in order to optimize water ﬂow and minimize chemical penetration into the subsurface. This site is also used to test the software, sensors, and hardware before deploying in Bangladesh.3 Sensor Sharing TechniquesSensor sharing will allow many people to beneﬁt from sensor network data collection, even with minimal sensor resources. We believe the following three technical approaches are particularly suited for enabling sensor sharing for sustainable development:(1) moving a smaller number of sensors around in a deployment to emulate density, (2) gradually removing redundant sensors from a deployment to go from dense to sparse deployments, and (3) leveraging shorter deployment cycles where possible. Here we describe each of these scenarios in greater detail, including a survey of our own and others’ work in implementing related or supporting algorithms.（1）Emulating DensityHuman-enabled mobility can be used to manually emulate the eﬀect of a dense deployment using fewer sensors. People can move a small set of sensors around in a ﬁeld in order to collect data for a dense spatial map of the ﬁeld. This technique will be appropriate only for sustainable development applications in which the phenomenon of interest changes very slowly, on the order of days or longer.（2）Dense to Sparse DeploymentsSome sensor network applications require a dense mapping of the environment. Once sensors are densely deployed and details of the phenomenon are revealed, we may see it is possible to capture suﬃcient information with fewer sensors, freeing sensors for deployment elsewhere. Here we describe applicable work which is ongoing in the sensor network community.（3）Short Deployment CyclesSome applications only require short-duration deployments and therefore are ideal for sensor sharing. Our deployment in Bangladesh is an example of an application with a short deployment cycle. We wanted to collect data to validate a hypothesis about diurnal variations, and so we wanted several days of data for analysis.4 ChallengesNumerous technical challenges arise in order to be able to quickly deploy and move sensors, primarily because the work to date has largely focused on static, long-running deployments.Given that we have the goals to emulate density, reduce dense deployments to sparse ones, and leverage short deployments cycles, we ﬁnd the following three challenges to be the most pertinent. Algorithms must be interactive and robust to human error. Faults in the system must be quickly identiﬁed to maximize the amount of good data received.Finally, systems must be made to be rapidly deployable.5 ConclusionWireless sensor networks have the potential to be a useful tool for sustainable development. This can be facilitated by the technical community if we focus on issues with developing wireless sensor net-works as a shared technology. 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