An Intelligent System for Real Time Crop Monitoring and Yield Estimation using Machine Learning

Abstract

Abstract: This ongoing effort aims to revolutionize the agricultural domain through the utilization of a microservices framework that leverages Spring Boot, REST API, and Bootstrap technologies. Its main goal is to offer real-time monitoring solutions, which are facilitated by an Oracle database for storing data acquired from various sensors, including those for weather, soil, and crop production. The overarching objectives include equipping farmers with instant insights into crop health and soil conditions, with a specific focus on increasing crop yields, reducing farming costs, and minimizing the environmental impact. The core functions of the project encompass data analysis to generate tailored farming recommendations, tracking the movements of pests and diseases, and predicting future crop yields. Expected advantages for farmers involve heightened productivity, costeffectiveness, sustainability enhancements, well- informed decision-making, and improved operational efficiency. As development advances, this endeavor holds significant promise for effecting a transformative influence on the agricultural sector.