Abstract: The safety and reliability of railway transportation largely depend on the structural integrity of the rail tracks, which are continuously subjected to dynamic loads, environmental effects, and material fatigue. Conventional manual inspection methods are inefficient, time-consuming, and often unable to identify hidden or developing faults in real time. To address these limitations, this project presents an Internet of Things (IoT)-based Railway Track Structural Health Monitoring System designed to ensure continuous, automated surveillance of track conditions using intelligent sensing and data communication technologies.

The proposed system employs a network of sensors such as strain gauges, vibration sensors, and ultrasonic sensors strategically installed along the railway tracks to measure strain, vibration, and surface irregularities. These analog signals are conditioned and processed by an ESP32 microcontroller, which serves as the central processing and communication unit. The system analyzes sensor data to detect deviations beyond predefined safety thresholds and transmits the results wirelessly via GSM or Wi-Fi modules to a central monitoring station or cloud-based dashboard. In the event of any abnormal condition, the system automatically generates real-time alerts through Telegram or SMS notifications, enabling prompt maintenance action and preventing potential derailments or failures.

The entire setup is powered through a low-power supply unit, with provisions for solar-based operation to enhance reliability in remote field environments. The collected data can be logged and analyzed on cloud platforms such as Thing Speak or Blynk, enabling visualization, trend analysis, and predictive maintenance using artificial intelligence

This project demonstrates a comprehensive integration of Electrical and Electronics Engineering (EEE) concepts, including sensor interfacing, signal conditioning, power electronics embedded systems, communication protocols, and automation control. By combining these technologies within an IoT framework, the proposed system offers a cost-effective, scalable, and sustainable solution for intelligent railway infrastructure monitoring. The developed prototype emphasizes the transition from conventional maintenance to smart, predictive, and data-driven maintenance, contributing significantly to improved safety, reliability, and operational efficiency in modern railway systems.

Keywords: Railway, cracks, Thing speak, Internet technology and IoT.

Downloads: | DOI: 10.17148/IJIREEICE.2026.14304