Wireless Sensor Network Research and Application In Agricultural Environment Monitoring
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1 Wireless Sensor Network Research and Application In Agricultural Environment Monitoring Meng Hao 1 Gu Lichuan 1 Sun Fukang 2 1.School of Information and Computer of Anhui Agricultural University, Hefei, China 2.School of Computer of Anhui University of Architecture, Hefei,China Abstract: This paper discussed wireless sensor network research based on embedded system design and 433MHz radiation data transmission method. It used the time sharing protocol in one direction communication and realized a low cost, small volume, low power and low data acquisition rate with time-period network application. By using GPRS, the node device can communicate with monitoring computer. In agricultural environment monitoring, especially in green house with thousands of squire meters, it can be used in environment monitoring. Key words: Sensor Wireless sensor network Agricultural monitoring Embedded system 1. Introduction At the present, wireless sensor network research and application are seriously concerned. Technological contents are gradually increased. In the research of wireless sensors research, many researchors have got great progress in the area of terminal design, communication, network protocol, power and application. Especially disposable and irretrievable sensors network applied in large area information collection [1], many products have realized the practical application stage, such as Zigbee [2]. Due to wide requirements of wireless sensors network application and differences in application properties, the establishment of practical application system has many technological difficulties needed to be solved [3,4]. The main indications involve production cost of system, volume of sensors, power support time, network protocol, capacity of data acquisition and communication distances. In the application of agricultural informatics, crop growth status, environmental conditions even pictures transmission by using of wireless sensors have wide application requirements. This research has certain value in agricultural environment data collection and application by using 433MHz with one direction data transmission wireless sensors. 2. System Structure and Target Position 2.1 System Structure In all wireless sensor products, some disposable and unretrievable type comes to front and can be used in large area monitoring. Our research wants to use normal digital elements and reduce its volume. In order to monitor the environment in connected greenhouse by wireless sensor network, we also need more sensors in disposition. This research uses 433MHz ASK modulation radio signal to transfer data from front sensor. The node uses the same frequency superheterodyne receiver to gather data and transfer data to up computer by GPRS network. So the whole system can be used in almost anywhere. [5,6] The wireless sensor module is consisted of data acquisition circuit and low-power consumption MCU and radio circuit and power system. The system work flow in figure 1.
2 Infrared Ray Configuration Receiver Light Sensor Air Temperature Sensor Soil Humidity Sensor Signal interface MSP430F149 MCU ASK Radio Module Batteries Fig.1 Wireless Sensor Terminal Structure Superheterodyne Receiver TCP/IP Model GPRS or CDMA 1X Model Solar Battery Power Management Li-battery ARM MCU LPC 2138 Real timer Fig.2 Node System Structure Considered the environment monitor are based on light, temperature, soil humidity in a green house, system uses light-sensitive diode to detect illumination intensity, diode sensor temperature to detect air temperature and soil humidity sensor to compose front sensors. All the signals can be connected to MSP430 MCU A/D pins. The data converted and coded can be transfer to node by the radio signal. Because the 433MHz radio transmitter can use built-in antenna and only use one direction transmission circuit, so the whole volume can be designed smaller and easy be built in a small box. In a green house, the environment must be controlled in suitable conditions for crop growthing. The growthing conditioned always have different value in large green house. Many this wireless sensors can be placed and grouped a network to detect all the parameter to be used in balance control. All wireless sensors can be designed in different address code or time sharing way in network build. The research used time sharing protocol, and data transmission time decided the number can be used in a segment. The button battery can be used to supply senor module power.
3 2.2 Target Position In some special situation, we neet more nodes to transmit data [7]. Considered every sensor is an independent transmitter, the most difficulty is the position of nodes and sensors placed. We can design the algrithm by reference to grid target position research. We can select either practical test method or following method in research. In recent, common methods in sensors blurring density are based on ambiguity matrix [8,9] and genetic algorithm evaluation [10]. For every instance I in workflow logs, what the algorithm needs is merely the order, not the concrete time, of the starting and ending events of every activity in the activity set AS(I). So the first step is to settle the log data to get the order of the starting and ending event of every instance activity. I i and I j are said to be repetitious if AS(I i )=AS(I j ) and the starting and ending events of every activity in I i and I j constitute the same time sequence. There may be many repetitious instances in the workflow log. Although these instances occur at different time, they have the same dependencies. In data preprocessing, log S 0 is divided into multiple Si, I i, I subsets S 1,S 2,,S n where j Si, I i and I j are repetitious and every set S j has one if its instances P kj as the representative so as to improve the efficiency of the succeeding algorithm. The dependency matrixes P 1,P 2,,P n, corresponding to subsets S 1,S 2,,S N, can be calculated. In the algorithm, the dependency among activities is taken as the instance item. Then the 1st candidate C = { d ij = 1 d ij = 0 d ij = 1: ak, a j V, i < j} set, denoted by 1, can be obtained [11,12]. According to definition, the support degree S 0 of every item of 1st candidate set C 1 is calculated and the item whose support degree is greater than threshold P s will be kept in 1st frequent set L 1. Considering the anti-symmetry of P 1,P 2,,P n, the following computation only deals with the upper triangular part of the matrix. 3. System Hardware 3.1 Sensor System used multi-feature transistor sensor. Temperature diode and illumination intensity can be changed to electric signals. Data can be compensated by software and system can botain exact temperature and illumination intensity. Soil humidity can be detected by conductance of the soil. The inside soil electrode can detect the signal and convert to humidity data by soil conductance model. All the data can be compressed and covered with protocol. Data transmission can be generated easily by radio module. 3.2 MCU MCU is low-power MSP430F149, MSP series MCU is 1.8v~ 3.6v working condition and the power consumption is decided by working mode and resource being used. Five low power working mode can be selected. In 1MHz clock, working current can be limited in 280 ua, in waiting mode, current is 0.7 ua. Lowest current is 0.1uA. By control the pins working mode, battery power can use for long time. In terminal system, MSP430 can complete A/D, data save, code, and other control work. The outer real timer can supply time sharing and help to produce data packet with protocol. 3.3 Radio Transmission
4 Considered sensor volume and battery power, terminal does not use double direction data transmission. Radio transmission circuit is a near distance data transmission. The circuit can be designed as simple as it can be. By ASK modulation signal can reduce the volume mostly in one direction transmission. The radio circuit can work in UHF wave band, 433MHz can be used freely. MCU control the system work in data transmission and save the power in other time. 433MHz ASK mode signal can reach 100 to 400 meters area or up. So the simple application has much advantage then the Bluetooth. The Lower cost can be realized. 3.4 Time Sharing Control System time sharing control is a base in this system data transmission. Considered the time sharing and address code are difficult in simple circuit and protocol design, the system use different time period transfer method. The MCUs in node and terminal can control sharing time period to transfer and receive data. There is an infrared ray receiver in circuit. All control configurations can be set by infrared ray remote controller and saved for ferment using. 3.5 Node Node is consisted of radio data receiver, ARM mcu, embedded software system, GPRS model, Power, antenna. If we consider node can work in unmanned situation, we must use large capacity backup batteries and solar battery system to supply the power. Radio data receiver is a superheat demodulating circuit. Local oscillator generates the local frequency, mixed with received carrier frequency, and then obtains the intermediate frequency. This signal can be amplified and demodulated, then output data. By using RX3310A, receiver sensitivity can be -100~102dbm, and by using surface acoustic wave devicer can be -100dbm steadily. RX3310A is an integrated circuit produced by Taiwan Hmark Company. It is designed specially in ASK remote control, data transmission and receiver. It contains low noise high frequency amplifier, frequency mixer, local oscillator, intermediate frequency amplifier, intermediate filter and comparer. Working frequency is MHz and maximum rate of data transmission is 9.6Kbps. RX3310A is dual-in-line package with 18 pins, signal input to pin 14 and data output from pin Monitor Device Monitor Device is consisted of PC, receive module. PC fulfils the main data processing and display tasks. It can receiver the data from the node, analysis the situation and transmits the instructions to control such as sun visor, light, temperature device and spray pump. Receive module is consist of GPRS with TCP/IP, received data from RS232 transfer to PC. 4. Software Wireless sensor terminal software can be divided by data receive, encode and transmission. Program with C can reduce development cycle. MSP430 can realize super low power working and Stand-by mode. So the software design must consider the power reduce and make batteries can work long. The monitoring software is designed by LabVIEW. It can be used conveniently is control and display area programming. The powerful display function can be used in graph (especially on
5 tendency chart) display and data processing. All process flow chart in software design indicate in figure3 and figure 4. Initialization Work Mode Set Power Detecting Start data acquisition Compensate, Encode System Initialization Set Node Work Mode Waiting and Recive Data Display Data Sand Control Instruction Start Data Transimission Enter Waiting Mode Fig.3 Sensor Termianl Work Flow Fig.4 Monitor System Work Flow 5. Conclusion This research uses MSP430 MCU sensors terminal design and greatly reduces system working power. Two button batteries can work for 2 years monitoring calculated by recording 20 times per day with 0.4 sec per time. Using MSP430 MCU chip kernel circuit covered with thick film, the volume is similar to the size of 9V battery and the production cost can be limited in tens of Yuan, which is easy for batch production. Application effects installed automatic connected greenhouses on our campus achieve the anticipated result of design. Installation position has been found to be close related to radiation distance and environmental control in the greenhouses existed dead space, so longer time in the control system was needed to get control quota. In the research of wireless sensors network, the volumes of sensors were the difficulties to be overcomed, battery life-span leaded to bigger volume of terminals and it hasn t better way to solve the problem. This research utilized common electric elements to realize more life-span and less volume of batteries, then to practical application. More researches are needed in the wireless sensors network application. 6. Acknowledgement This paper is supported by the Science and Technology Project of Educational Department of Anhui Province (KJ2007B046,KJ2008A065,KJ2008B111). 7. References 1 Ravelomanana V. Extremal properties of three-dimensional sensor networks with applications. IEEE Trans. on Mobile Computing, 2004,3(3):
6 2 Huang CF, Tseng YC. A survey of solutions to the coverage problems in wireless sensor networks. Journal of Internet Technology, 2005,6(1): Lin FYS, Chiu PL. A near-optimal sensor placement algorithm to achieve complete coverage/discrimination in sensor networks. IEEE Communications Letters, 2005,9(1): Megerian S, Koushanfar F, Potkonjak M, Srivastava MB. Worst and best-case coverage in sensor networks. IEEE Trans. on Mobile Computing, 2005,4(1): Cortes J, Martinez S, Karatas T, Bullo F. Coverage control for mobile sensing networks. IEEE Trans. on Robotics and Automation, 2004,20(2): Gupta H, Das SR, Gu Q. Connected sensor cover: Self-Organization of sensor networks for efficient query execution. In: Gerla M, ed. Proc. of the ACM Int l Symp. on Mobile Ad Hoc Networking and Computing (MobiHOC). New York: ACM Press, Kar K, Banerjee S. Node placement for connected coverage in sensor networks. In: Crowcroft J, ed. Proc. of the Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks. Sophia-Antipolis: IEEE Press, Ye F, Zhong G, Cheng J, Lu SW, Zhang LX. PEAS: A robust energy conserving protocol for long-lived sensor networks. In: Stankovic J, Zhao W, eds. Proc. of the Int l Conf. on Distributed Computing Systems (ICDCS). Providence: IEEE Press, Wang X, Xing G, Zhang Y, Lu C, Pless R, Gill C. Integrated coverage and connectivity configuration in wireless sensor networks. In: Akyildiz IF, Estion D, eds. Proc. of the ACM Int l Conf. on Embedded Networked Sensor Systems (SenSys). New York: ACM Press, Adlakha S, Srivastava M. Critical density thresholds for coverage in wireless sensor networks. In: Tachikawa K, ed. Proc. of the IEEE Wireless Communications and Networking (WCNC). New Orleans: IEEE Press, Megerian S, Koushanfar F, Potkonjak M, Srivastava MB. Worst and best-case coverage in sensor networks. IEEE Trans. on Mobile Computing, 2005,4(1): Cortes J, Martinez S, Karatas T, Bullo F. Coverage control for mobile sensing networks. IEEE Trans. on Robotics and Automation, 2004,20(2):
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