
Data Analytics System for Irrigation Alert, Fertilizer and Pesticide Recommendation towards Sustainable Agriculture
Author(s) -
K. Sumathi,
P. Deepalakshmi,
K. Selvarani
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d1103.1284s219
Subject(s) - agriculture , analytics , productivity , business , agricultural science , irrigation , precision agriculture , fertilizer , agricultural engineering , agricultural productivity , computer science , agricultural economics , environmental science , engineering , data science , economics , economic growth , ecology , chemistry , organic chemistry , biology
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.