Intelligent Food Delivery Time Prediction

This paper presents a machine learning approach to accurately predict food delivery times by analyzing factors such as the delivery person’s age, ratings, vehicle type, and the distance between the restaurant and delivery location. Using a Long Short-Term Memory (LSTM) neural network trained on historical delivery data, the model captures complex relationships to improve prediction accuracy. The system is implemented as a Python Flask web application, allowing users to input delivery parameters and receive real-time predictions, while administrators can manage users and feedback securely. The proposed solution aims to enhance operational efficiency, optimize logistics, and improve customer satisfaction in the competitive online food delivery industry.