Data Analytics System for Irrigation Alert, Fertilizer and Pesticide Recommendation towards Sustainable Agriculture
K. Sumathi1, P. Deepa Lakshmi2, K. Selvarani3
1Dr. K. Sumathi, Assistant Professor, Department of CS & IT, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
2Dr. P. Deepa Lakshmi, Professor, Department of CSE, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
3Dr. K. Selvarani, Assistant Professor, Department of Agricultural Sciences, Kalasalingam Academy of Research and Education College, Krishnankoil (Tamil Nadu), India.
Manuscript received on 01 December 2019 | Revised Manuscript received on 19 December 2019 | Manuscript Published on 31 December 2019 | PP: 551-557 | Volume-8 Issue-4S2 December 2019 | Retrieval Number: D11031284S219/2019©BEIESP | DOI: 10.35940/ijrte.D1103.1284S219
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Ministry of statistics and program implementation says that, the agriculture sector’s contribution to the Gross Domestic Product (GDP) decreased gradually from 54% in 1950- 51 to 15.4% in 2015-16. Farmers are suffering because of nonavailability of information and no proper guidance (advisory services). Farmers in rural areas are detached from technology and essential agricultural support services needed to carry out in farming activities and their productivity per acre is low due to lack of adopting recent mechanisms and technology usage. This paper presents a Data Analytics System for Irrigation Alert, Fertilizer and Pesticide Recommendation. The system is developed using modern digital technologies by bringing the necessary supporting elements in one place and to deliver necessary insights to farmers throughout crop cultivation to improve the farming actives. The proposed system includes 2 modules a) External Intelligence Module b) Data Analytics Module. In first module, data is gathered from farmer’s dataset, irrigation partners, pesticide vendors, fertilizer dataset. The second module will work on the grounds of output being “yes” of EIS, will generate alert regarding Irrigation, pesticides and Fertilizer Recommendation. The proposed system offers personalized advisory services using communication devices to maximize the crop yield and to minimize the cost of production.
Keywords: Data Analytics, Pesticide Recommendation System, Fertilizer Recommendation System, Irrigation Alert System.
Scope of the Article: Data Analytics