Godfrri Croos, N2026-02-082025-12https://rda.sliit.lk/handle/123456789/4566Sri 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.enAgriSenseIoT-Integrated CropRecommendationPrice Forecasting SystemUsing MachineThesis