Analysis of Geolocation Dataset and Fertiliser Availability to Farmers at Minimum Cost
Chintan Rajvir1, Rajasekaran Rajkumar2, Jolly Masih3, Paviter Singh Matharu4
1Chintan Rajvir, School of Computer Science and Engineering, Vellore Institute of Technology, India.
2Rajasekaran Rajkumar, School of Computer Science and Engineering, Vellore Institute of Technology, India.
3Jolly Masih, Erasmus School of Economics, Erasmus University, the Netherlands, Mosaic Company India Pvt. Ltd., India.
4Paviter Singh Matharu, Erasmus School of Economics, Erasmus University, the Netherlands, Mosaic Company India Pvt. Ltd., India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 07 June 2019 | Manuscript published on 30 June 2019 | PP: 2115-2118 | Volume-8 Issue-8, June 2019 | Retrieval Number: H7526068819/19©BEIESP
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© 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: According to World Bank’s survey, India has the largest area of arable land of approximately 156.4 million hectares which is about 57% of total land in the country. The demand for agricultural products is high in India which corresponds to high use of fertilisers. Both natural and synthetic fertilisers are equally predominant. The primary issue with fertilisers is how to buy the fertilisers with lesser cost where cost of travelling and transportation plays a major role. The poor market research and unawareness of the farmers makes them vulnerable while buying fertilisers. They levy unnecessary costs on fertilisers and increase their expenditure for the yield. We analysed this growing concern for a vast agricultural country like India and came up with proper insights and solution. Our solution involves analysis of distances between geolocations or places where fertilisers are available (e.g. fertiliser shop or retail store for fertiliser) and allowing the farmers to go select amongst those available storesthe nearest and best place to purchase the fertilisers.
Keywords: Geolocation Dataset, Agricultural Products
Scope of the Article: Analysis of Algorithms and Computational Complexity