Farmer Logistics Connector For Truck Sharing And Route Matched Load Optimization
DOI:
https://doi.org/10.64751/7zsv5m92Abstract
Agricultural transportation plays a vital role in connecting farmers with markets, but conventional logistics management often suffers from poor coordination, inefficient vehicle utilization, and increased transportation costs. Manual communication methods such as phone calls and local agents frequently result in delayed deliveries, empty return trips, and limited visibility of available transport resources. To address these challenges, this research proposes the Farmer Logistics Connector for Truck Sharing and Route Matched Load Optimization (FLCTS), a web-based platform that digitally coordinates truck sharing among farmers and truck owners. The system is developed using React.js for the frontend, Django Representational State Transfer (REST) Framework for backend services, and My Structured Query Language (MySQL) for centralized data storage. It provides secure user registration, administrator approval, role-based access control, truck posting, route-based transport matching, and transport request management through Application Programming Interfaces (APIs). The centralized database enables efficient storage and retrieval of user, truck, and request information while ensuring transparency and data consistency. The proposed system minimizes empty vehicle trips, improves truck capacity utilization, reduces fuel consumption, and decreases transportation delays through structured digital coordination. Additionally, it enhances communication between stakeholders, supports secure information sharing, and provides real-time visibility of transport availability. Experimental implementation demonstrates that the platform improves operational efficiency, strengthens agricultural supply chain coordination, and offers a scalable, reliable, and cost-effective solution for rural transportation management. The proposed framework contributes to sustainable agricultural logistics by replacing traditional manual processes with an intelligent, transparent, and technology-driven
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.







