Machine Learning For Agribusiness Using GIS
Sahana D Gowda1, Niveditha N M2, Amulya M P3, Namitha A R4
1Sahana D Gowda Department of Information Science, Adichunchanagiri University-BGSIT,BG Nagar Mandya, India.
2Niveditha N M, Department of Computer Science, Adichunchanagiri University-BGSIT,BG Nagar Mandya, India.
3Amulya M P, Department of Information Science, Adichunchanagiri University-BGSIT,BG Nagar Mandya, India.
4Namitha A R, Department of Computer Science, Adichunchanagiri University-BGSIT,BG Nagar Mandya, India.
Manuscript received on 14 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 July 2019 | PP: 1249-1251 | Volume-8 Issue-2, July 2019 | Retrieval Number: B1779078219/19©BEIESP | DOI: 10.35940/ijrte.B1779.078219
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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: In present days we have discussed about the emerging concept of smart agriculture that makes agriculture more efficient, effective and farmers save money and time with the help of high precision algorithms and Geographic Information System (GIS).The component that drives it is GIS with Machine Learning the logical field that enables machines to learn without being carefully customized. It has developed together with huge information advances and elite registering to make new chances to disentangle, measures, and comprehends information concentrated procedures in farming operational conditions. For instance, ranchers use accuracy GPS on the field spare manure. Ranchers use precision agribusiness since they can lessen the proportion of manure fertilizer. Moreover, satellites and robots assemble vegetation, topography and atmosphere information from the sky. This information can go into developing maps for better fundamental activity.
Keywords: Geographic Information System, Machine Learning, Precision Farming.
Scope of the Article: Machine Learning