Data mining and wireless sensor network for agriculture pest/disease predictions

Tripathy, A K and Adinarayana, J and Sudharsan, D and Merchant, S N and Desai, U B and Vijayalakshmi, K and Raji Reddy, D and Sreenivas, G and Ninomiya, S and Hirafuji, M and Kiura, T and Tanaka, K (2011) Data mining and wireless sensor network for agriculture pest/disease predictions. In: World Congress on Information and Communication Technologies, WICT 2011, 11-14, December 2011, Mumbai; India.

507.pdf - Published Version

Download (691kB) | Preview


Data driven precision agriculture aspects, particularly the pest/disease management, require a dynamic crop-weather data. An experiment was conducted in a semi-arid region to understand the crop-weather-pest/disease relations using wireless sensory and field-level surveillance data on closely related and interdependent pest (Thrips) - disease (Bud Necrosis) dynamics of groundnut crop. Data mining techniques were used to turn the data into useful information/knowledge/relations/trends and correlation of crop-weather-pest/ disease continuum. These dynamics obtained from the data mining techniques and trained through mathematical models were validated with corresponding surveillance data. Results obtained from 2009 & 2010 kharif seasons (monsoon) and 2009-10 & 2010-11 rabi seasons (post monsoon) data could be used to develop a real to near real-time decision support system for pest/disease predictions.

[error in script]
IITH Creators:
IITH CreatorsORCiD
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Data Mining; Pest/Disease Management; Precision Agriculture; Wireless Sensor Networks
Subjects: Others > Agricultural engineering
Others > Electronic imaging & Singal processing
Physics > Electricity and electronics
Computer science > Computer programming, programs, data
Divisions: Department of Electrical Engineering
Depositing User: Team Library
Date Deposited: 29 Oct 2014 06:59
Last Modified: 07 Dec 2016 04:38
Publisher URL:
Related URLs:

Actions (login required)

View Item View Item
Statistics for RAIITH ePrint 507 Statistics for this ePrint Item