Final Year Project

Project Title

AgriVerse: AI-Based Agricultural Commodity Price Prediction Platform

Description

Developed an AI-powered platform to predict agricultural commodity prices using machine learning techniques, including LSTMs and ensemble models. The system integrates real-time data pipelines with a full-stack architecture, enabling continuous data ingestion, processing, and prediction. A multilingual dashboard was designed to ensure accessibility for diverse, non-technical users. The project aimed to address price volatility in agricultural markets by providing reliable, data-driven forecasts to support better decision-making for stakeholders. Key outcomes included improved prediction accuracy across multiple commodities and the successful deployment of an end-to-end system capable of handling real-world data. The project demonstrates the practical application of AI in solving domain-specific challenges at scale while prioritizing usability and impact.