AgriSense: An IoT-Integrated Crop Recommendation and Price Forecasting System Using Machine Learning

Abstract

Sri Lankan smallholders make planting and selling decisions in the presence of shifting monsoon patterns and volatile local markets. AgriSense is an end-to-end system that integrates a low-cost IoT field device with cloud-based machine learning to support both crop selection and price planning. The device collects plot-level measurements of soil chemistry and condition, together with ambient data and location, and streams these to a backend designed to tolerate intermittent rural connectivity. In the cloud, a supervised crop-recommendation model trained on a soil feature set produces a ranked shortlist of suitable crops with calibrated probabilities.