A Software-Driven AI Approach to Logistics Process Automation

This paper presents the design and development of an AI-enabled, software-based system for automating logistics op- erations, aiming to upgrade conventional supply chain processes. The solution includes two dedicated mobile applications—one for customers and the other for delivery personnel—along with a comprehensive, web-based admin dashboard. All components are integrated to function cohesively, ensuring efficient management and real-time synchronization across the logistics chain.

The system provides complete lifecycle support for shipments, from initial booking to final delivery confirmation. Key features include user-friendly shipment request forms, automatic identi- fication of pickup and drop-off points via the Google Maps API, and optimized routing through Dijkstra’s algorithm to reduce travel time. Real-time location tracking, powered by continuous GPS updates, enables both clients and administrators to monitor deliveries with accuracy and transparency.

For administrative users, the platform offers a powerful control panel to manage shipment approvals, assign delivery fees, allocate drivers, and oversee real-time progress. To minimize manual intervention, an AI-driven chatbot is integrated to re- spond to common customer queries, including delivery tracking, estimated arrival times, and issue reporting.

A built-in analytics module further enhances decision-making by visualizing key metrics such as delivery volume by location, commonly used routes, cost breakdowns, and preliminary rev- enue estimates. By merging automation, live data processing, and AI-driven insights, the platform delivers a scalable, efficient solution for optimizing logistics operations and modernizing traditional supply chain systems.

Logistics automation, Firebase, Google Maps API, React Native, AI chatbot, route optimization, data analytics, Dijkstra algorithm

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