The paper discusses an IoT-based railway management system for detecting cracks on railway tracks, monitoring platform availability, fire detection and suppression, train movement control, and automatic level crossing gate operations. The proposed system integrates various sensors (IR, ultrasonic, camera, fire), Arduino microcontrollers, DC motors, relays, Zigbee communication, and image processing techniques. The crack detection module employs IR sensors, ultrasonic sensors, and image processing algorithms to identify cracks or obstacles on the tracks. The platform monitoring module uses IR sensors to track platform occupancy and enable efficient train scheduling. The fire detection module incorporates fire sensors and activates water pumps, sprinklers, and emergency train compartment detachment mechanisms. The train movement module utilizes DC motors for precise acceleration, deceleration, and movement control. The level- crossing module automatically opens and closes gates based on train arrival and departure times. The system provides real- time communication and alerts through Node MCU and Zigbee technology. The article draws attention to the severe damage done by track-related accidents, which are among India's top causes of loss of life and property. The paper stresses how vital it is that railways are safe. This paper talks about the various problems with the Indian railway network and why there is a need for an efficient technology for track fault detection. Moreover, this paper’s focus extends to the more innovative approaches, including UAVs fitted with cameras and LiDAR sensors for aerial inspection of rails, new materials for improved track lifespan and strength, implementation of Internet of Things (IoT) devices enabling real-time information-gathering and robotic systems for autonomous maintenance duties on tracks.


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    Titel :

    IoT-enabled Asset Monitoring and Optimization Railway System


    Beteiligte:
    Tabassum, Husna (Autor:in) / J, Jenita (Autor:in) / Hunagund, Samreen (Autor:in) / S, Sahana (Autor:in) / Santolli, Swati Shrikanth (Autor:in) / Abdul Rehman, Syed (Autor:in)


    Erscheinungsdatum :

    27.07.2024


    Format / Umfang :

    746302 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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