Soil Quality Monitoring and Crop Prediction Using IOT and Machine Learning

Abstract

People are pressured for time in today's fast-paced environment, and technology assists them in a variety of ways. Agriculture is the primary industry in India. As a result, in the current environment, increasing output or production is critical. When it comes to determining certain chemical features of soil that have an immediate impact on plant growth, traditional farming faces various obstacles. Another critical factor to consider is the effect of timely water supply on plant output. The soil alkalinity and electrical conductivity are measured with PH electrodes. This study also looked into the real-time detection of soil variables and the location of chemical properties like pH, humidity, temperature, and soil moisture using a Raspberry Pi as a controller. Semi-supervised learning will be carried out in a methodical manner using the Q-learning algorithm. We used a range of samples in the experiment to show how to apply the indicated performance.