Consumer demand is always fluctuating, even more for bananas. Accurate consumer demand forecasts are crucial for banana farms to decide when and how many bananas are to be harvested. In this proposed research, we study the historical data of banana consumption at various levels and identify the influencing factors such as seasonality, consumer behaviors, weather conditions, etc. Through integrating AI/ML with statistical methods and optimization techniques, accurate forecasting models and methods will be developed and implemented. Ultimately, a data driven intelligent demand forecasting system will be developed for farms to forecast banana consumption at various levels.