IoT and SVM-based Smart Irrigation System for Sustainable Water Usage
A. Sherly Alphonse, Vimal Kumar, N. Meenakshisundaram, Anvar Shathik J, S. Gomathi
Abstract
The typical farming procedure requires a significant quantity of water use, which results in water waste. An automatic watering technology is desperately required to decrease the amount of water wasted during this time-consuming activity. Because of the advancements in machine learning (ML) and the Internet of Things (IoT), there is a significant benefit to developing a smart platform that does this work successfully and with minimum human intervention. It is recommended in this paper that landowners use a minimal amount of involvement in an IoT-enabled machine learning-trained recommender system for effective water consumption. The Internet of Things (IoT) sensors are put in the agricultural field to gather accurate information about the soil and environmental condition. Upon collection, the information is moved and saved in a fog system, which uses machine learning algorithms to analysis the information and provide watering recommendations towards the producer. A built-in relay switch has been included into this suggestion system in order to make it more resilient and adaptable. The results of the experiments show that the suggested system works admirably on both our own gathered information and also the agricultural information from NIT Raipur.