IoT and AI Enabled Agriculture: Monitoring, Predictive Analysis and Crop Optimization

Abstract

The purpose of this paper is to examine how Internet of Things (IoT) technologies are transforming agriculture by improving monitoring, predictive analytics, and crop optimization. Real-time data from sensors and IoT devices is used to evaluate critical parameters like soil quality, weather, and pest management to optimize crop yield. The focus of the study is on data-driven crop yield optimization, AI-based crop rotation strategies, and weather-responsive farming. Significant improvements were observed in the results, with a 33.33% increase in crop yield (tons per hectare), a 50% increase in early pest detection rates, and a 21% increase in Grade 'A' harvest quality. The importance of it in modern agriculture is due to the contributions made by these advances to profitable and sustainable practices. Farmers, agronomists, and policymakers can benefit from this research, which advocates for the adoption of IoT to address food security challenges in an evolving agricultural landscape.