Design of a Real-Time Logistics Route Monitoring and Optimization System based on AI and Web-GIS

Abstract

This study presents a system integrating Artificial Intelligence (AI) with Web Geographic Information Systems (Web-GIS) to optimize real-time logistics routes. The system dynamically updates delivery paths based on traffic data, vehicle constraints, and delivery priorities, thereby increasing efficiency and reducing travel time. Evaluated through simulation scenarios, the system demonstrated significant improvements in delivery speed, fuel consumption, and customer satisfaction compared to conventional static routing methods. The results suggest that AI-enhanced Web-GIS solutions are effective tools for modern and sustainable urban logistics management. Future research aims to improve predictive accuracy and expand scalability across diverse geographic areas.