TRAINS: Train and Passenger Real-Time Analytics and Integration Network System Using NeuRaiSya with BhaiCha Algorithm and PINNs Applications

Current Philippine railway systems face significant challenges in real-time monitoring and effective management of both train movements and passenger flow. These challenges often lead to inefficiencies, safety concerns, and financial losses due to outdated monitoring systems and a lack of predictive capabilities. Addressing these issues, the NeuRaiSya System was developed to enhance the oversight and management of trains and passenger movements. The system assists engineers and operators by providing tools for real-time tracking and prediction of train movements, thereby preventing potential issues and optimizing passenger flow to improve train traffic and maximize railway revenue. The system achieves these goals by gathering sensor data, including accelerometer, gyroscopic, and tilt angle measurements, which are simulated and analyzed using the PINNs application for train anomaly detection and prediction. This BhaiCha algorithm employs a coding matrix to convert sensor data into actionable insights about the train's status and passenger distribution. The system's graphical user interface (GUI) supports real-time monitoring by visualizing train movements and conditions. Simulation results demonstrate that the BhaiCha algorithm effectively generates signal codes that accurately reflect the status of trains and passenger flow, addressing the critical needs of modern railway systems. The implementation of this system shows significant potential to improve safety, efficiency, and financial management in railway operations.