Automated Irrigation System Based on LoRa and ML for Marginal Farmers

Abstract

Background & Objective:: India is one of the foremost agricultural producers in the world; on the other hand, the consumption of water for agricultural purposes in India has been among the highest in the world. Indiscriminate use of inadequate irrigation techniques has led to a critical water deficit in the country. Now with the development of (IoT) Precision Farming and Precision Irrigation are becoming very popular. This paper proposes a cost-effective Automated Irrigation System based on LoRa and Machine Learning, which can be of great help to marginal farmers, for whom agriculture is hardly a profitable venture, mainly due to water scarcity. Methods: In this automated system, LoRa technology is used in Sensor and Irrigation node, in which sensors collect data on soil moisture and temperature and send it to the server through a LoRa gateway. Then the data is fed into a Machine Learning algorithm, which leads to correct prediction of the soil status. Results: Hence, the field needs to be irrigated only if and when it is needed. Conclusion: The system can be remotely monitored using a web application that can be accessed by a mobile phone.