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@article{194597,
        author = {BENNILA THANGAMMAL and HAVINASH RAJAN T and SHURTHICK R and VAIKUNDAM PRASSATH G},
        title = {ACOUSTIC SIGNAL ANALYSIS FOR RAILWAY TRACK CRACK DETECTION IN IOT FRAMEWORK},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6931-6936},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194597},
        abstract = {Keeping railway tracks in good condition is essential for the safe and smooth operation of trains. Cracks that remain undetected can cause major accidents, delays in service, and heavy financial losses. This project proposes an IoT-based railway track crack detection system that uses acoustic wave propagation to identify faults at an early stage with better accuracy. In this system, sensor nodes are installed along the railway track. Each node includes a piezoelectric sensor that sends acoustic waves through the rail and a microphone sensor that receives those waves after they travel through the structure. When there is a crack or any structural defect, the received signal shows noticeable changes compared to normal conditions. These signal variations are captured, processed, and transmitted by a microcontroller to a cloud platform. The data is then uploaded to the Blink IoT cloud, where it can be monitored, stored, and analyzed in real time. A user interface is developed to classify the condition of the track as minor, medium, or major cracks, helping maintenance staff understand the severity quickly and take action. An RFID module is also added to detect train arrival and departure, improving coordination and system awareness. Overall, the proposed system offers a cost-effective, non-destructive, and continuous monitoring solution that strengthens railway safety through early crack detection and remote access to information.},
        keywords = {Railway Track Monitoring, Crack Detection, Acoustic Waves, Piezoelectric Sensor, IoT, Blink IoT Cloud, RFID, Structural Health Monitoring.},
        month = {March},
        }