Enhancing Online Cab Dispatch Efficiency: A KNN Approach to Demand Prediction and Resource Optimization

This work concentrates on the development of cab dispatch software to provide a platform for scheduling cab rides. Key objectives include establishing a booking process, implementing real-time notifications to keep users informed of their booking status, improving the driver dashboard with clear visibility of ride requests, and making sure of the security of user data through industry-standard encryption techniques and MySQL database integration. One major problem faced by traditional cab dispatch systems is the insufficient availability of cabs, leading to longer wait times for users and underutilization of cab resources. The variation between cab supply and user demand further worsens this issue, impacting user satisfaction and system efficiency. To address these challenges, this work proposes a predictive solution utilizing machine learning algorithms. KNN model has been implemented and integrated in this application. By analysing historical ride data stored in the system's database, this model can forecast future demand patterns. These predictions enable the system to dynamically adjust cab dispatch strategies, optimizing cab allocation to meet potential anticipated demand.