Paper Title
IoT Based Railway Track Inspection System Using GPS and Sensors

Abstract
Ensuring the safety and reliability of railway infrastructure is critical to preventing accidents and improving operational efficiency. Traditional track inspection methods are often time-consuming, labor- intensive, and may not detect issues in real-time. This paper presents an Internet of Things (IoT)-based railway track inspection system that leverages a combination of sensors and GPS technology for continuous monitoring. The proposed system utilizes vibration sensors, ultrasonic sensors, and tilt sensors to detect anomalies such as cracks, misalignments, and track displacements. GPS modules are integrated to accurately geo-tag the location of each detected fault, enabling precise maintenance interventions. Data collected by the sensors is transmitted wirelessly to a central monitoring station, where it is analyzed in real-time. The system is designed to be mounted on inspection trolleys or trains, allowing for seamless integration into existing railway operations. Experimental results demonstrate the effectiveness of the system in identifying track defects with high accuracy and minimal latency. This approach not only enhances safety but also optimizes maintenance schedules and reduces inspection costs. Keywords - IoT (Internet of Things), Railway track inspection, Sensors, GPS, Real-time monitoring, Track anomaly detection, Structural safety, Predictive maintenance, Wireless data transmission, Smart transportation systems.