Developed by Prof Dharmendra Singh amp Team Sponsored by RailTel IITR Centre of Excellence in Telecom RICET Department of Electronics amp Communication Engineering Indian Institute of Technology Roorkee Roorkee247667 India ID: 570220
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Agriculture Information System for ICTDeveloped by Prof. Dharmendra Singh & Team Sponsored by: RailTel-IITR Centre of Excellence in Telecom (RICET)Department of Electronics & Communication Engineering, Indian Institute of Technology Roorkee, Roorkee-247667, IndiaE-mail: dharmfec@iitr.ernet.in, Ph.No.: +91- (0) 1332-285695
Introduction
One of the major deficiencies in the modernization efforts of agriculture in India is lack of technical guidance to farmers. However, the farmers are involved in growing same crop from centuries and have a lot of experience, but the final outcome is always affected by the changing weather conditions, soil moisture conditions, crop health, crop diseases and other such factors. The timely information on all these factors can be of great help to the farmers and the significant amount of time, effort, and cost can be saved. ICT can be very much helpful in this information dissemination. This project proposal tries to fulfil this need. As all these issues are highly localized in nature and setting up the ICT infrastructure in the localized fashion can proves to be very costly, the use of cloud computing technology can be very helpful in this direction.
Developed Model
Methodology
Development Team
Some Results
One module of AIS
is developed and tested for Haridwar District for the year of 2014, implementation for other Districts of Uttarakhand is under process.Other Modules are in developing phase.Web based and SMS based AIS development is in process.
Flow Chart of Overall Methodology
Objective
Prof. Dharmendra Singh (dharmfec@gmail.com)
Mr. Tasneem Ahmed (tasneemrke@gmail.com)
Ms. Shruti Gupta (shruti2306@gmail.com)Mr. Shashi Vardhan Naidu (msvnaidu92@gmail.com)Mr. Gaurav Kapatia (gkapatia@gmail.com)Mr. Rachit Sharma (rachitsharma1234@gmail.com)
The basic objective of the project is to provide the agro-meteorological data, location, and disease information to the agricultural administers through the automatic analysis of optical and SAR data based upon ICT in cost-effective way. To make the developed system to be accessible to various agricultural administrators located on various different stations, each of the station has to be equipped with necessary hardware and software infrastructure. In addition to cost, the expertise for setting of the infrastructure is also required. To handle this problem, it is planned to provide this service through cloud environment to make the service hassle free and cost effective to the end users.it is planned to provide the information to end users by SMS or Web based.
Server
Crop Identification
Bare Filed
Crop/Vegetation Filed
Classified Image
Area Estimation
Decomposition
Rotation
Without Rotation
Pauli
3D
HA/α
4D/4D Modified
Fusion Algorithm
Data Fusion
Selection of Bands
View
Classification
Supervised
Unsupervised
Minimize the Changes
MODIS/OPTICAL Images
Band & Indices Values
RISAT/PALSAR Images
Scattering Image
Intensity Image
Agricultural Parameter Estimation (Soil Moisture, Crop Health etc)
Time Series Analysis
Observed Change
SMS Web Based
(Information to End User)
Proposed Layer Structure
SaaS Layer:
Developed Application for agricultural information and disease forecasting
Browser
GUI
PaaS
Layer:
Development and execution environment for agricultural information and disease forecasting system
Data base Management System
Operation support
Responsible for all image processing, data processing, and other analysis activities
IaaS
Layer:
Server
Storage
Network
Operating system
Terminal and other
Developed Agriculture Information System
Agriculture Information System (AIS) is developed and tested for whole Haridwar District (Uttarakhand, India), for the year of 2014.
In the beginning,
y
ear, month and
region of interest
(name of District) need to be selected by clicking NDVI button to see the area information.
NDVI images of selected and previous year will be displayed.
Greenness information of the area (NDVI Profile)
will be obtained for
five years (after selecting the month).
Sample moisture maps are displaying for approx. 15 different locations with different dates (after selecting the Place).
After clicking on classification button, the selected region of interest will be classified into Water, Urban and Vegetation classes.
Classified images of selected and previous year will be displayed.
Land cover areas (Water, Urban and Vegetation) are shown in square Kilometers.
Changes can be observed by clicking on Change Maps button.
Change maps of Water, Urban and Vegetation will be displayed and change and no change areas are shown in square kilometers.
Agriculture Information System
Concluding Remarks