Guided Analytics Platform for Southern Region of Tamilnadu Farmer Fraternity
K.Sumathi1, P. Deepalakshmi2, K. Nagarajan3
1K. Sumathi, Assistant Professor, Department of CS & IT, Kalasalingam Academy of Research and Education College, Krishnankoil, Virudhunagar (Tamil Nadu), India.
2K. Nagarajan, Principal Consultant, Tata Consultancy Services, Chennai (Tamil Nadu), India.
3P.  Deepalakshmi, Professor, Department of CSE, Kalasalingam Academy of Research and Education College, Krishnankoil, Virudhunagar (Tamil Nadu), India.
Manuscript received on 24 November 2019 | Revised Manuscript received on 18 December 2019 | Manuscript Published on 30 December 2019 | PP: 551-559 | Volume-9 Issue-1S4 December 2019 | Retrieval Number: A11231291S419/19©BEIESP | DOI: 10.35940/ijeat.A1123.1291S419
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Abstract: Agriculture has its role to play in our economy like any other sector but the unique role and importance is comparatively high than the other sectors. Most of the families who are farmers in our country live in rural areas and find themselves aloof from technological world. Essential agricultural support services needed to be carried out in farming activities are left unaware for them. Moreover, farmer’s income and productivity can be improved through extension and advisory services which would be of greater support. With the advent of technological resources that is suitable, cost effective, user friendly and scalable for the farmers certain farming activities can be improved. This paper intends to propose a data analytic platform using modern digital technology enabling effective collaboration among farmer fraternity and peripheral partners. The platform ensures of delivering enhanced insights to the agricultural community with essential guidance and tips to improve with on high crop yield; forecast and report right time for sowing and irrigation; corrective measures to be performed during pest attack so that the farmers enrich their agricultural activities with the support of efficient decision making system.
Keywords: Machine Learning Techniques, Big Data Analytics, Decision Making System for Farmers and their Ecosystem.
Scope of the Article: Machine Learning