Publication Type : Journal Article
Publisher : International Journal of Sensors Wireless Communications and Control
Source : International Journal of Sensors Wireless Communications and Control”, Volume 10, Issue 3 (2020): 345-353.
Url : https://www.ingentaconnect.com/content/ben/swcc/2020/00000010/00000003/art00008
Campus : Coimbatore
School : School of Physical Sciences
Department : Mathematics
Year : 2020
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.
Cite this Research Publication : Loganathan, Selvam; Perumal, Kavitha, "Automated Irrigation System Based on LoRa and ML for Marginal Farmers," International Journal of Sensors Wireless Communications and Control”, Volume 10, Issue 3 (2020): 345-353.