International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 04 | Apr 2025
p-ISSN: 2395-0072
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Autonomous Railway Track Monitoring Robot with Real-Time Alerting and Live Video Streaming Pratik Prakash Student, Electronics and Communication Engineering VIT Bhopal University ---------------------------------------------------------------------***--------------------------------------------------------------------This paper proposes a smart Railway Track Crack Detection Abstract - Railway infrastructure plays a vital role in the
Bot using the STM32F103C8T6 microcontroller as the core processing unit. The bot utilizes an ultrasonic sensor to monitor track conditions continuously and identifies major cracks based on predefined threshold values. A GSM module is used to transmit alerts along with GPS-based location data whenever a critical defect is detected. Furthermore, an ESP32-CAM module enables live video streaming and provides manual control features via a wireless web interface, enhancing the bot's flexibility in difficult terrains.
transportation system, requiring regular monitoring to prevent accidents caused by track cracks. This paper presents the design and development of an autonomous Railway Track Crack Detection Bot using STM32F103C8T6 as the central controller. The system employs an ultrasonic sensor to detect major cracks on the railway track by continuously measuring the surface distance. Upon detecting a significant crack, the bot automatically halts and transmits the real-time location using a GSM module integrated with GPS data acquisition. Additionally, an ESP32-CAM module is deployed to provide live video streaming and manual movement controls via a web-based user interface, enabling remote intervention if needed. The bot is programmed to start moving automatically upon activation, ensuring initial autonomous operation. The motor driver circuit, controlled through GPIO pins of the STM32 microcontroller, enables forward, backward, and directional movement based on commands received or detection events. Emphasis is placed on robust communication between modules, precise crack classification, and real-time alerting to minimize human inspection effort and enhance railway safety. The proposed system demonstrates an efficient, low-cost, and scalable solution for proactive railway track maintenance. Future enhancements may include machine learning-based crack severity analysis and multi-sensor fusion to improve detection reliability under various environmental conditions.
The bot is designed for autonomous operation, with the capability to start movement automatically upon activation. In the event of a major crack detection, the bot halts and transmits critical information to a remote monitoring station. By integrating real-time sensing, wireless communication, and manual control functionalities, the proposed system aims to provide a cost-effective and scalable solution for enhancing railway safety. This research builds upon earlier studies [2][3], improving upon limitations through the integration of modern microcontrollers and IoT modules. 1.1 PROBLEM IDENTIFICATION Railway transportation plays a vital role in the movement of goods and passengers due to its cost-effectiveness and efficiency. However, track-related failures such as cracks, misalignments, or deformations are among the leading causes of railway accidents. Traditional manual inspection methods are time-consuming, labor-intensive, and often fail to detect defects promptly, especially in remote or less accessible areas. This delay in detection can lead to catastrophic accidents, loss of life, and major financial setbacks. Moreover, most existing systems lack real-time monitoring and automated alert mechanisms, making it difficult to ensure continuous track health surveillance. Therefore, there is a significant need for an autonomous, real-time, and efficient railway track monitoring system that can automatically detect track cracks, locate them accurately using GPS technology, and alert authorities through GSM communication. Additionally, live video surveillance is essential for remote monitoring and manual control during critical inspection activities. This project aims to address these challenges by developing a low-cost, reliable robotic solution using STM32 microcontroller, ultrasonic sensors, GPS, GSM, and ESP32-CAM modules for integrated crack
Key Words: Railway Track Monitoring, Crack Detection, STM32F103C8T6, Ultrasonic Sensor, GSM Module, GPS Tracking, ESP32-CAM, Autonomous Bot
1.INTRODUCTION Railway transportation systems form the backbone of many nations' economic and social development. The maintenance of railway tracks is crucial to ensure the safety and efficiency of train operations. Cracks or structural defects in railway tracks can lead to catastrophic accidents, resulting in loss of life and property. Therefore, the early detection of track faults is a major research focus [1]. Traditional inspection methods often involve manual labor, which is timeconsuming, expensive, and prone to human error. To address these limitations, automation and real-time monitoring solutions are increasingly being explored.
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