Title:Automated Irrigation System Based on LoRa and ML for Marginal Farmers
VOLUME: 10 ISSUE: 3
Author(s):Selvam Loganathan* and Kavitha Perumal
Affiliation:Department of Computer Science, Loyola College, Vettavalam, Tiruvannamalai Dt, Department of Computer Science, Paavendar College of Arts and Science, Attur, Salem DT
Keywords:Agriculture, automated irrigation system, farming, IoT, lora, machine learning.
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.
