Agriculture Recommendation System Using Collaborative Filtering

The agricultural sector plays a crucial role in the Moroccan economy, making a significant contribution to the GDP and directly influencing economic growth. However, it faces various challenges despite the efforts of the authorities. In this context, our work aims to propose solutions using artificial intelligence techniques to assist farmers in selecting crops suitable for their land while considering environmental factors. The recommendation system is designed to suggest which crops to grow based on location, soil properties, and weather details operates by analyzing historical data on crop performance across various locations. It uses a method known as collaborative filtering, adapted to the context of agricultural data, to make these recommendations. This recommendation system works by learning from historical data on how different crops perform in various environmental conditions. It then uses this knowledge to predict which crops are likely to be successful in similar conditions elsewhere. This process involves sophisticated data analysis techniques but aims to provide actionable, evidence-based advice to farmers and agricultural planners on optimizing crop selection for any given location.