Aanchal Patil@Aanchal

AgriSense AI is an intelligent crop advisory system built to help farmers in Haryana make faster, data-driven decisions about irrigation and crop health. Most smallholder farmers lack easy access to satellite-based agricultural insights, relying instead on guesswork or delayed government advisories. AgriSense AI closes that gap by combining remote sensing data with a conversational AI agent that explains findings in plain language. The system pulls Sentinel-2 satellite imagery to compute NDVI (Normalized Difference Vegetation Index) and NDWI (Normalized Difference Water Index) values for specific districts in Haryana, giving a real-time picture of vegetation health and soil moisture. This data is fed into an AI reasoning layer powered by the Fireworks AI API running the GLM-5p2 model, which interprets the raw indices and generates clear, actionable advisories, telling farmers whether a field needs irrigation, is under stress, or is healthy, and what steps to take next. A Flask backend handles district-wise data processing and serves the advisory logic, while a clean, Dockerized HTML dashboard presents the information through three distinct UI states so farmers or extension workers can quickly check field status without technical expertise. The entire stack is containerized for easy deployment, making it practical to scale across additional districts or states. By making satellite agriculture accessible and understandable, AgriSense AI aims to reduce water waste, improve crop yields, and support more resilient farming decisions for Haryana's agricultural communities.

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