agriculture decision support system
DESCRIPTION
Krishi sense agriculture decision support systemTRANSCRIPT
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Prepared By:
Pankaj Khodifad(09BEC027)
Guided By:
Prof. Sachin Gajjar and Prof. Nirav Modi
(Electronics and Communication department)
Major Project
Institute of Technology
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Outline
• Introduction
• Knowledge Base Agriculture System
• KrishiSENSE
• EZ430RF2500 Kit
• Demo
• Reference
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Agriculture : A Complex System
Productivity is affected by variability in the following six groups:
• Yield variability
• Field variability
• Soil variability
• Crop variability
• Variability in anomalous factors
• Management variability
Precision Agriculture (PA) is to manage these variability
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FIELD IRRIGATION MODULE Type & Variety of Crop
Type of Soil
Date of sowing
Soil Temperature
Atmospheric Temperature
Solar Radiation Duration
Wind Velocity
Ambient Humidity
Rainfall Data and Agro climate zone
Leaf/Plant Image
pH & other N, P, K Value
Crop Specific Information (Data Base) Optimum Timing for Irrigation
Best Suitable weather
Ideal Stages Schedule
TYPES OF DISEASE & INFECTION (Data Base)
PEST CONTROL MODULE
FARM LAND NUTRITION
MODULE
N, P, K AND OTHER MICRONUTRIENTS & THEIR EFFECTS
& SUPPLIES (Data Base)
Number of Days left for Irrigation
Irrigation not required
Arrange within week
Severely required
Suggestion of schedule of activities like cutting, picking etc.
Suggestive schedule for pesticide
Preventive application of pesticide
Suggestive Type & Quality of Fertilizer & micro inputs
Suggestion of Best suitable crop
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Knowledge Base • Evapotranspiration Rate ET0 Calculation
• Hargreaves Equation is used (As it needs minimum parameter)
• Estimation of equation constants CH and EH for particular location is done
using fuzzy based method to improve the accuracy.
• Constants CH and EH values are found for the locations.
Solar radiation Ra is considered constant for the given
• location and converted in the unit mm/day.
amean
E
H RTTTCET H )8.17()( minmax0
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Algorithm
Estimation of soil water deficit using water balance approach (Weather based method)
Dc = Dp + ETC – P - Irr
Where,
Dp = Soil water deficit on the previous day in (mm)
Dc = Soil water deficit today in (mm)
ETc = Crop evapotranspiration rate for current day in (mm)
P = Gross precipitation (rainfall) for the current day in (mm)
Irr = Net irrigation amount for the current day in (mm)
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Option # 1
Desktop Application
www.krishisense.org
USB MySQL Database
WSN Coordinator
Node
WSN Node
WSN Node
WSN Node
WSN Node
Temperature Humidity
Solar Radiation
Wind Velocity
Working Modality of KrishiSENSE
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EZ430RF2500 Kit Introduction
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EZ430RF2500 Kit Introduction
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EZ430RF2500 Kit Introduction
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Wireless Sensor Networks
24 April 2014 11
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Option # 3
Wireless to GPRS/GSM
Module & Light Wind Sensors
Desktop Application
www.krishisense.org
MySQL Database
WSN Coordinator
Node
WSN Node
WSN Node
WSN Node
Temperature
Humidity
Solar Radiation
Wind Velocity GPRS/GSM Module
Cellular Network
RE
RE
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AP ED RE ED
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S1
RE2 RE3
RE4 RE6
N7 N10
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Reference • http://www.ti.com/product/msp430f2274
• http://www.ti.com/tool/ez430-rf2500
• http://www.ti.com/tool/msp-exp430g2#buy
• http://www.ti.com/lsds/ti/microcontroller/16it_msp430/hardware_and_software.page?DCMP=MSP430&HQS=Tools+OT+ez430
• http://www.digikey.com/product-search/en/sensors-transducers/ambient-light-sensors/1966828?k=light%20sensor
• http://www.digikey.com/product-detail/en/HIH-5031-001/480-3284-2-ND/2061067
• http://www.mysmartprice.com/mobile/micromax-a68-smarty-4.0-msp2451
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