Hybrid Deep Learning for Smart Agriculture Forecasting

This coursework explores the development of a hybrid model for agriculture, targeting precision farming with a focus on Egypt’s Al-Sharkia region. Topics include spatial classification using CNN, weather forecasting with LSTM, and rule-based crop recommendations integrated with Sentinel-2 satellite data and meteorological inputs. Results demonstrate high accuracy, reliable predictions, and enhanced crop-resource alignment compared to existing models. Challenges such as dependence on diverse...