Digital Farmer Assistant

  • Akhilesh Pathak, Mrs B.Ida Seraphim

Abstract

The Indian Agriculturalists have been considering soil fertility reduction as a major setback to Indian agriculture output and its growth, uncalculated farming or excessive use of chemicals - synthetic fertilizers and insecticides - is responsible for soil degradation and decreasing crop yield. Several studies and reports suggest that the farmers who use their approximations to use fertilizers and crops to grow, degrades the soil fertility much faster and causes a very low yield. To counter this problem of soil degradation and low crop yield, a system is developed to recommend the farmers which crop would be beneficial for the soil or which crop would be most profitable for both farmer and the soil. The portable device, synced with a server checks for soil quality which can be kept at the farmer's house. The system performs calculations and estimations using Machine Learning and Data Mining Algorithms, and then recommends crops for that particular time and soil conditions on farmer’s smartphone. The system aims to reduce the farmers' pain of going across cities just to get the soil checked from the government’s Soil Testing Laboratories and getting results after 2-3 weeks which is valid for a period of 5 years. The goal is to improve the overall crop yield and to maximize the profit gain from the land with minimal effect on the soil health.

Keywords: IoT, Machine Learning, Agriculture, Soil Analysis, Mobile Application.

Published
2020-05-06
How to Cite
Akhilesh Pathak, Mrs B.Ida Seraphim. (2020). Digital Farmer Assistant. International Journal of Advanced Science and Technology, 29(06), 2418 - 2426. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/13658