Automation of Agriculture Support Systems using Wisekar: Case study of a crop-disease advisory service

Computers and Electronics in Agriculture

Volumn 122, Issue , 2016, Pages 200-210

  Sarangi, Sanat ^a   Umadikar, Jayalakshmi ^b   Kar, Subrat ^a  

^a INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY MADRAS   (India)

Author keywords

Agriculture; Application framework; Call centre; Crop disease; Wisekar

Indexed keywords

AGRICULTURAL MACHINERY; CROPS; INFORMATION USE;

AGRICULTURAL PRODUCTIONS; APPLICATION FRAMEWORKS; CALL CENTRES; CROP DISEASE; HETEROGENEOUS SYSTEMS; INFORMATION AND COMMUNICATION TECHNOLOGIES; MACHINE-TO-MACHINE COMMUNICATIONS; WISEKAR;

AGRICULTURE;

AGRICULTURAL PRODUCTION; AUTOMATION; CALL CENTER; CONCEPTUAL FRAMEWORK; INFORMATION AND COMMUNICATION TECHNOLOGY; SOFTWARE; WORLD WIDE WEB;

CHENNAI; DELHI; INDIA; TAMIL NADU;

EID: 84958225953     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2016.01.009     Document Type: Article

References (15)

1. Anandaraja, N., Sriram, N., Kathiresan, C., Sebastian, S., Vadivel, E., 2009. Web cum mobile based dynamic market information support for Agri-Horti produces: linking the farmers with market. In: International Conference for Internet Technology and Secured Transactions (ICITST), pp. 1-6.
2. Anandaraja N., Sankri S., Sriram N., Venkatachalam R. TNAU agri tech portal: content design and validation. CSI Commun. 2013, 21-25.
3. Chang, K., Yau, N., Hansen, M., Estrin, D., 2006. A centralized repository to slog sensor network data. In: Proc. Int. Conf. Distrib. Comput. in Sens. Syst., San Francisco, CA, USA.
4. Chen X.-Y., Jin Z.-G. Research on key technology and applications for internet of things. Phys. Proc. 2012, 33:561-566.
5. Glendenning, C.J., Babu, S., Asenso-Okyere, K., 2010. Review of agricultural extension in india - are farmers "Information Needs Being Met?". IFPRI Discussion Paper 01048, pp. 1-35.
6. Grosky W., Kansal A., Nath S., Liu J., Zhao F. Senseweb: an infrastructure for shared sensing. IEEE Multimedia 2007, 14(4):8-13.
7. Hannuna S., Anantrasirichai N., Subramanian S., Prashant S., Jhunjhunwala A., Canagarajah C.N. Agriculture disease mitigation system. ICTACT J. Commun. Technol.: Special Issue Next Gen. Wirel. Networks Appl. 2011, 2(2):363-369.
8. Jhunjhunwala, A., Umadikar, J., Prashant, S., 2013. A new personalized agriculture advisory system. In: Proceedings of the 19th European Wireless Conference (EW), pp. 1-6.
9. Pachube IOT Data Infrastructure and Community, (last visited: 09.09.15). http://umbrellium.co.uk/initiatives/pachube/.
10. Sankaran S., Mishra A., Ehsani R., Davis C. A review of advanced techniques for detecting plant diseases. Comput. Electron. Agric. 2010, 72(1):1-13.
11. Sannakki S.S., Rajpurohit V.S., Nargund V., Kumar A., Yallur P.S. Leaf disease grading by machine vision and fuzzy logic. Int. J. Comput. Technol. Appl. 2011, 2(5):1709-1716.
12. Sarangi, S., Kar, S., 2013. Wireless sensor knowledge archive. In: IEEE International Conference on Electronics, Computing and Communication Technology (CONECCT), pp. 1-6.
13. Surendrababu V., Sumathi C., Umapathy E. Detection of rice leaf diseases using chaos and fractal dimension in image processing. Int. J. Comput. Sci. Eng. (IJCSE) 2014, 6(1):69-74.
14. TongKe F. Smart agriculture based on cloud computing and IOT. JCIT: J. Convergence Inform. Technol. 2013, 8(2):210-216.
15. UCI Machine Learning Repository, 2015. (last visited: 09.09.15). http://archive.ics.uci.edu/ml.