Market Demand Forecasting and AI-Based Crop Recommendation for Farmers

Abstract

Agriculture plays a crucial role in our society food security and economic stability and reactivity. However, farmers are facing many types of problem and challenges in selecting the right crops due to the market demand, leading to financial losses and resource misallocation. This research paper explores the use of Artificial Intelligence (AI) and Machine Learning (ML) to forecast market demand and provide data-driven crop recommendations. To analyzing our market demands, climate conditions/changes, soil health, and economic factors, the proposed system predicts the most profitable crops for cultivation. Machine learning models such as Time Series Forecasting and Regression Analysis are utilized to ensure most demand prediction. The results demonstrate that AI-driven recommendations can analyze agricultural decision- making, reduce risks management, and enhance productivity. This study shows the predict of AI in changing traditional farming practices, enabling farmers to make informed choices that connect with market needs and promote sustainable agriculture. This approach promotes sustainable agriculture, enhances productivity, and bridges the gap between latest farming practices and modern technological advancements.