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

Proceedings of the 2011 World Congress on Information and Communication Technologies, WICT 2011

Volumn , Issue , 2011, Pages 1229-1234

  Tripathy, A K ^a   Adinarayana, J ^a   Sudharsan, D ^a   Merchant, S N ^a   Desai, U B ^a,d   Vijayalakshmi, K ^b   Raji Reddy, D ^b   Sreenivas, G ^b   Ninomiya, S ^e   Hirafuji, M ^c   Kiura, T ^c   Tanaka, K ^c  

^a INDIAN INSTITUTE OF TECHNOLOGY BOMBAY   (India)

^b ACHARYA N G RANGA AGRICULTURAL UNIVERSITY   (India)

^c NATIONAL AGRICULTURAL RESEARCH CENTER   (Japan)

^d INDIAN INSTITUTE OF TECHNOLOGY HYDERABAD   (India)

^e UNIVERSITY OF TOKYO   (Japan)

Author keywords

Data Mining; Pest Disease Management; Precision Agriculture; Wireless Sensor Networks

Indexed keywords

DATA DRIVEN; DATA MINING TECHNIQUES; POST-MONSOON; PRECISION AGRICULTURE; REAL-TIME DECISION SUPPORT SYSTEMS; SEMI-ARID REGION; SURVEILLANCE DATA; WIRELESS SENSOR;

ARID REGIONS; ARTIFICIAL INTELLIGENCE; ATMOSPHERIC THERMODYNAMICS; CROPS; DECISION SUPPORT SYSTEMS; DYNAMICS; FORECASTING; INFORMATION TECHNOLOGY; MATHEMATICAL MODELS; WIRELESS SENSOR NETWORKS;

DATA MINING;

EID: 84863158659     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WICT.2011.6141424     Document Type: Conference Paper

References (20)

1. Agrawal, R., Imielinski, T., Swami, A.N.(1993), Mining Association Rules between Sets of Items in Large Databases." SIGMOD. June 1993, 22(2): pp. 207-16.
2. Agrawal R. and Mehta S.C.(2007), Weather Based Forecasting of Crop Yields, Pests and Diseases - IASRI Models, Journal of Indian Society of Agricultural Statistics, 61(2): pp. 255-263.
3. AgriSens (2007), SPANN Lab. WSN project report, Electrical Engineering Department, IIT Bombay, Available at, Http://www.ee.iitb.ac.in/spann/agrisens/ (Accessed on 23 March 2009).
4. AgroMet-Cell: Entomology Work 2008-09. AgroMet-Cell, Agriculture Research Institute, ANGRAU, Hyderabad, Annual Report, pp. 57-69.
5. Das A., Ng W. K. and Woon Y. K. (2001), Rapid association rule mining, CIKM '01, Proceedings of the tenth international conference on Information and knowledge management (CKIM'01), November 5-10, 2001, Atlanta, GA, USA, pp. 474-481.
6. George H. J. and Pat L. (1995), Estimating Continuous Distributions in Bayesian Classifiers. Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann, San Mateo. pp.338-345.
7. George N. A. (2005), Plant Pathology. Elsevier Academic Press. 5th ed, ISBN 978-0120445653.
8. Georg R., Rudolf K., Martin S., Peter W. (2008), Data Mining with Neural Networks for Wheat Yield Prediction. P. Perner (ed.), Springer LNAI, Vol. 5077, pp. 47-56.
9. Kendre M. S., Patange, N. R., Neharkar P. S., and Telang S M. (2010), Occurrence of Thrips plami, a vector of bud necrosis disease of groundnut in Marathwada region, Journal of Soils and Crops, 10:2, pp. 226-230.
10. Madden L., Gareth H, Frank V, Den B. (2007). Study of Plant Disease Epidemics. American Phytopathological Society. ISBN 978-0890543542.
11. Mitchell T. M. (2010), Generatvie and Discruninative Classifier: Naive Bayes and Logistic Regression, In Machine Learning, McGraw Hill (Draft of January 19, 2010), pp. 1-17.
12. Prabhakar T.V, Jamadagni H. S., Sahu A, Prasad R. V. (2010), "Lessons from the Sparse Sensor Network Deployment in Rural India", 11th International Conference on Distributed Computing and Networking (ICDCN' 10).Springer LNCS, Vol- 5935, pp. 104-115.
13. Prasad, R D V J. (2009), Thrips Transmitted Viral Diseases in Groundnut and Management, Proceeding of workshop Changing Insect Pest Scenario and Management strategies in Different Crops, Hydearbad, pp. 89-97
14. Reddy, D D R and Ravindra, B.(2008), Groundnut Insect Pests, Diseases, Nutritional Disorders, Acharya N.G. Ranga Agricultural University, Information Bulletin No.4, pp. 20-36
15. Singh Faujdar and Oswalt D.L.(1992), Major Diseases of Groundnut, ICRISAT-skill development series No.6, pp. 50-36.
16. Shekh, A.M., Patel, H.R., and Pandey, V. (1999), Predicting the outbreak and spread of pests and diseases using weather parameters. Dept. of Agri. Meteorology, Gujarat Agriculture University Anand, Annual Research Report, Vol.2, pp. 249-255.
17. Sudharsan D., Adinarayana J., Tripathy A. K., Desai U. B., Merchant S. N., Ninomiya S.,Hirafuji M., Kiura T. and Tanaka K.,(2011),GeoSense: Geo-ICT and Wireless Sensor Network based Dynamic Real-time System for Precision Agriculture (2011); Proceeding of CIGR (Commission Internationale du Genie Rural) Conference CIGR2011, September 19-23, 2011, Tokyo, Japan.
18. U-Agri (2008), Ubiquitous Agriculture, CDAC, Hyderabad (Project Report accessed on 21 February 2009) http://www.ubicomp.in/uagri
19. Vijayalakshmi K., Reddy Raji D., Varma N.R.G. and Pranuthi G. (2009), Weather based pest and disease forwarning models in groundnut in the context of climate change, Workshop Proceedings: Impact of Climate Change on Agriculture, ISPRS Archives XXXVIII-8/W3: pp. 48-50.
20. Wu, L., Damicone, J. P., Duthie, J. A., and Melouk, H. A. (1999), Effects of temperature and wetness duration on infection of peanut cultivars by Cercospora arachidicola. Jounal of Phytopathology 89: pp. 653-659. (Pubitemid 29373194)