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1.
International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME 332 CONTEXT- AWARE WIRELESS SENSOR GRID IMPLEMENTATION FOR AGRICULTURE Jayant P. Pawar1 , Dr. Prashant V. Ingole 2 , Aparna R. Kadam3 1 (Associate Professor, Dept of EXTC, Atharva College of Engineering, Mumbai, M.S, India) 2 (Principal, G.H.Raisoni college of Engineering and Management, Amravati, (M.S,) 3 ( Asst.Professor, Dept of EXTC,Atharva college of Engineering,Mumbai(M.S, India) ABSTRACT Context aware computing means sensing the context and other input channels, taking smart decisions and feedback tracking from the context [1] .Agriculture is a very rich context aware domain and is a fundamental area of human society in which research and development has still a wide scope. Wireless sensor network (WNS) is the promising technology for instrumentation and control. In this paper, context aware water irrigation system models have been developed and implemented using WNS and grid computing [7]. The results clearly indicate the maintenance of moisture for long duration which helps in crop growth. Alternately, we can say, it reduces the water requirement in next watering process and helps to reduce the water requirement. Keywords: pyramid structure, Context –Awareness. I. INTRODUCTION Agriculture is very important aspects of human society. The modern technologies like wireless sensor networks, grid computing, context-aware decision making systems are equally important to change the agricultural practices for better productivity. How to improve the productivity and irrigation area in the available water is a good tread off. The smart decision in irrigation depends upon the ambient temperature, soil temperature, and water holding capacity of the soil, humidity and types of crops. Growth and productive status of crop are also deciding factors in irrigation. The wire free nature of WSN is suitable for agriculture. To measure the parameters related to irrigation and transmission of data over wireless channel, WSN is a good option. Context-awareness appears as a promising idea for increasing usability of web services. INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATION ENGINEERING & TECHNOLOGY (IJECET) ISSN 0976 – 6464(Print) ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April, 2013, pp. 332-337 © IAEME: www.iaeme.com/ijecet.asp Journal Impact Factor (2013): 5.8896 (Calculated by GISI) www.jifactor.com IJECET © I A E M E
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME 333 Context aware sensor network also makes energy efficient network which can helps in arriving at a smart decision in active agriculture process. Grid computing is a computer network in which each computers resources can be shared with every other computer in the system. This technology is also useful in our system to take the advantages of information technology for resources sharing and accessing the data word widely The integration of WSN, context aware computing and grid i.e. context aware sensor grid [1], add the precision and helps in the decision making and control processes in agriculture. The rest of the paper is organized as follows: In section II pyramid context aware model has been explained. Implementation of our system has been explained in section III. Results are analyzed in section IV. The paper has been concluded in section V. II. PYRAMID -CONTEXT AWARE MODEL Let the agriculture information space be represented as a concept pyramid with the vertices representing the various contexts of information retrieval [3]. The simple pyramid context aware model for water irrigation is shown in figure. Fig. 1 : Concept Pyramid In this information space the nature of query may be single dimension query, edge level query and space level query. The query is like “What is the soil type in this location?. ” so the client is referring only the land context and the context point present exactly at the land vertex is the single dimension query. In the edge level the client is requesting information regarding two contexts at a time. e.g.- the query which crops are feasible for this particular water availability? So here the client refers to two contexts, crop and water and hence the context point is present somewhere on the edge connecting the crop and the water context. When the client needs information regarding three contexts simultaneously, it lies in space level. For example the query how much irrigation should be done for this particular crop in this particular soil?, has a context point present in the concept space between land, crop and water contexts. The context migration is shown in table 1.In some cases where land is not a major deciding factor or posses uniform properties, or crop may be same, then we can replace this context by humidity. TABLE I. CONTEXT MIGRATION TABLE Context Point Context edge Context plane Crop CL,CT,CW (1,2,3) 1,2,3 Land LT,LW,LC (4,6,1) 1,3,4 Water WC,WT,WL (3,5,6) 2,3,4 temp TC,TL,TW (2,4,6) 1,2,4
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME 334 III. IMPLEMENTATION OF CONTEXT AWARE SENSOR GRIDE A conceptual system layout of distributed infield WSN is illustrated in figure 2. For soil moisture measurement, the gypsum sensor is used. It absorbs the water and provides a decent range of resistance which is proportional to amount of moisture in the soil. In our experiment, we calibrate it from 40K ohm to 330K ohm in the range of zero to 100% moisture. To Measure the temperature, we have used LM35C while to measure the humidity we used SY-HS230. To transfer these data wirelessly, we have used Zig Bee module X Bee [14] which outdoor range is 300 feet for 1mw transmit power. At computer side, module is configured as routers. Digi International [14] offers a convenient tool X- CTU for programming XBee module. With this Fig 2: System layout. Software, the user will be able to upgrade the firmware, update the parameters, and perform communication testing easily. In this implementation, we have embedded node to which the sensors are attached. The LPC2148 ARM microcontroller has built in ADC & DAC. All sensors readings are processed by ADC and then data is transferred by the Zigbee module, which is mounted on the same board .Two such similar boards are used for different zones. Server PC is wirelessly connected to two nodes placed in the farm in two different zones. Sensors generates large amount of data. The data base designed in MS Access and nodes carry out data processing by embedded C language. The collected data is then processed, and analyzed at the server node by the computer. Context algorithm and GUI is implemented in Visual Basic 6.0. The database can maintained and analyses for future use at some remote personal computer .To make current sampled data available at remote location it is uploaded on internet using VB.NET. Thus data sharing principle of grid computing is implemented. ANSI C compiler used to generates the object code that matches the efficiency and speed of assembly programming. This complier used to write microcontroller application in C language. Extensions in compiler help full access to all resources of the microcontroller. The compiler translates C source files into relocatable object modules which contain full symbolic information for debugging with circuit emulator. In addition to the object file
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME 335 the compiler generates listing file which may optionally include symbol table and cross reference information. IV. RESULTS AND ANALYSIS Figure 3 shows Graph 1, Graph 2, and graph3. In these graphs, temperature and soil moister readings are showing on the middle of the bar, while they are at the time of beginning of the bar. Graph 1 shows the soil moister, temperature and irrigation on time with duration on 21st November, 2012 while Graph 2 shows reading from 5 PM to 12.30 AM. From these observations it is cleared that, due to temperature rise soil moisture increases slowly during the irrigation, but after sunset, soil moisture increases sharply in another test bead. So it is clear that if we control the irrigation according to temperature and soil moister, in the same amount of water we can extend the next irrigation. Graph 3 shows the reading on next day i.e. 22 November using another test bed having same soil and plant. On 22nd November we used another algorithm which used 25% soil moister as a triggering level for irrigation when temperature goes on or above the threshold level, here it is 30 degree Celsius. From Graph 3 it is cleared that, while we reduce the irrigation during high temperature and adding that duration in next irrigation time i.e. when temperature goes below 30 degree Celsius or soil moisture goes below 25%, at the end of the day soil moisture gets increased.
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME 336 Figure 3: Graph 1, Graph 2, Graph 3. V. CONCLUSION AND FUTURE WORK From the above graphs we can conclude that context awareness help in designs making in precise water irrigation process. Soil moister evaporation will be very fast if the system will test in high temperature. Here we consider the minimum soil moister at 25% and it is adjustable as per the available water and need of the crop.Our future works will consider the context parameters and comparison of results for productive irrigation process. REFERENCES [1] Aqeel-Ur-Rehman And Zubair A. Shaikh, Towards Design Of Context-Aware Sensor Grid Framework For Agriculture, To Appear In The Fifth International Conference On Information Technology (Icit 2008), Xxviii- Waset Conference, April 25 27, 2008, Rome, Italy. [2] W. Zhang, G. Kantor, And S. Singh, Integrated Wireless Sensor/Actuator Networks In An Agricultural Application, In Proc. 2nd Acm Intl Conf. Embedded Networked Sensor Systems (Sensys 04), Acm Press, 2004, Pp.317.8 [3] Prashant Ingole, Jayant Pawar, Hrishikesh Vhatkar,” Context Aware, Mobile Phone Based Sink Model Of Wireless Sensor Network For Indian Agriculture, Advances In Computing,Communication And Control Communications In Computer And Information Sciences,Vol. 361,2013,Pp 301-308 [4] P.V.Ingole ,J.P.Pawar,Role of information technology in global agro business, second international conference at nirma institute of technology,1-4jan2000 [5] Carlos De Morais Cordeiro, Dharma Prakash Agarwal, Adhoc Sensor Net-Works: Theory And Applications World Scientific Publication. [6] Chandrasekaran S, Dipesh Dugar M, Jitendra Kumar Jain D,Kamlesh Jain S, Dinesh Kumar Jain N. Context Aware Mobile Service Deployment Model Of Agricultural
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International Journal of
Electronics and Communication Engineering & Technology (IJECET), ISSN 0976 – 6464(Print), ISSN 0976 – 6472(Online) Volume 4, Issue 2, March – April (2013), © IAEME 337 Information System For Indian Farmers. 2010 International Journal Of Computer Applications(0975-8887) Volume 1-No.29 [7] Hock Beng Lim. Yong Meng Teo,Protik Mukharjee . Sensor Grid : Integration Of Wireless Sensor Networks And The Grid, Proceeding Of The Ieee Conference On Local Computer Networks 30th Anniversary [8] T. Pering, P. Zhang, R. Chaudhri, Y. Anokwa, And R. Want,The Psi Board: Realizing A Phone-Centric Body Sensor Network, In Proc. 4th Bsn 2007, Germany. [9] D. Cavalcanti, C. Cordeir, D. Agarwal, B.Xie And Anup Kumar,Issues In Integrating Cellular Networks, Wlan And Manets: A Furturistic Heterogeneous Wireless Networks, Ieee Wireless Communication, Iune 2005, Vol. 12, No.3, Pp 30-41 [10] Tapankumar Basu, Vijaya R. Thool, Ravindra C. Thool, And Anjali C. Birajdar, Computer Based Drip Irrigation Control System With Remote Data Acquisition System, In Proc. 4th World Congress Conf. Computers In Agriculture And Natural Resources, Usa, July 2006. [11] Y. Kim, R.G. Evans, And W. Iversen, Remote Sensing And Control Of Irrigation System Using A Distributed Wireless Sensor Network, Ieee Trans.Instrumentation And Measurement, 2007 [12] A. Baggio, Wireless Sensor Networks in Precision Agriculture, In Proc. Acm Workshop Real-World Wireless Sensor Networks, 2005. [13] T.Wark, P. Corke, P. Sikka, L. Klingbeil, Y Guo, C. Crossman, P. Valencia,And D. Swain, Transforming Agriculture Through Pervasive Wireless Sensor Networks, Ieee Pervasive Computing, Pp. 5057, April-June 2007. [14] www.digi.com [15] Pimentel,Berger, et al. (October 2004)."Water resources: agricultural and environmental issues".BioScience 54 (10): 909. doi:10.1641/0006-3568(2004)054[0909:WRAAEI]2.0.CO;2 [16] Mr. Shrinivas R. Zanwar and Prof R. D. Kokate, “Advanced Agriculture System” International Journal of Advanced Research in Engineering & Technology (IJARET) Volume 3, Issue 2, 2012, pp. 111 - 118, Issn Print: 0976-6480, Issn Online: 0976-6499 [17] Naresh Kumar Reddy.Beechu, B.Siva Hari Prasad, B.Y.V.N.R.Swamy, “Innovative Water Saving Agriculture By Using Resources” International Journal of Electronics and Communication Engineering &Technology (IJECET) Volume 3, Issue 2, 2012, pp. 227 - 237, Issn Print: 0976- 6464, Issn Online: 0976 –6472 [18] Prof. (Ms) Manisha Shinde-Pawar And Prof. (Mr) Chandrashekhar Suryawanshi, “Integrating Gis And Knowledge Management Resources In Indian Agriculture: Social And National Concern For Information Sharing” International Journal Of Management (IJM) Volume 4, Issue 1, 2013, pp. 258 - 265, Issn Print: 0976-6502, Issn Online: 0976-6510
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