IoT Enabled Intelligent Load Balancing System for Railway Wagons through Artificial Intelligence
Year: 2024
Type: article
Abstract: This research paper presents an innovative system that integrates IoT (Internet of Things) and AI (Artificial Intelligence) technologies to address the critical issue of load balancing in railway wagons. Traditional systems focus on post-event detection of overloading or under loading, which poses safety risks and inefficiencies. In contrast, our solution leverages IoT-enabled load cells to continuously monitor wagon loads in real-time and utilizes AI-driven algorithms such as Genetic Algorithms and Reinforcement Learning—to optimize load distribution dynamically. The system ensures balanced loading across wagons, preventing overloading and underutilization, improving safety, fuel efficiency, and operational effectiveness. The IoT sensors provide real-time data that is processed by AI models to predict and balance load allocation, thus minimizing the risk of infrastructural damage and enhancing wagon capacity utilization. Initial testing shows a 95%reduction in load imbalances, a 20% decrease in loading time, and improved fuel economy by 10%. This research contributes to railway freight logistics by offering an AI- powered solution for intelligent load management, ensuring safety, efficiency, and cost-effectiveness.
Authors: Prof.(Dr.)Vikas Singhal, Sajal Rai, Rishav Raj, Raza Karim, ManojKumar Mishra, Ritik Raj
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405020920