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.
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ISSN 0976 – 6464(Print)
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2. 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
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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

3. 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

4. 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.

5. 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.
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