AI-driven Smart Logistics for Rural Development

Abstract

This work discusses an AI-driven smart logistics framework tailored for rural development. The system retrieves historical market data, accepts user input for product details, stock quantity, and destination, and then suggests optimal pricing, vehicle type, and route. By leveraging AI, this model enhances efficiency, reduces costs, and promotes economic growth in rural areas. The proposed system aims to streamline supply chain operations in rural regions by integrating predictive analytics, intelligent decision-making, and automated logistics planning. The paper highlights the methodologies, experimental results, and future enhancements required to scale the system effectively.