Railsense

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  FLOWDIAGRAM

Frequent hot axle failures in trains cause accidents and delays, which inspired us to build Railsense, a real-time safety system to detect and prevent such incidents. Our solution uses infrared sensors to continuously monitor axle temperatures, assigns each axle a unique ID, and transmits real-time alerts to the loco-pilot and control centers through LoRa and 4G/5G connectivity. While building the project, we integrated sensors with ESP8266 modules, designed a central node for data collection, and implemented a threshold-based warning system that classifies conditions as normal, warning, or danger. During development, we faced challenges like sensor calibration, power management, and ensuring reliable low-latency communication. We are proud of creating a working prototype that is low-cost, automated, and capable of reducing human effort while improving railway safety. Through this journey, we learned how to integrate hardware with IoT, manage real-time data, and collaborate effectively as a team. Moving forward, we aim to conduct large-scale field testing with Indian Railways, add predictive analytics using machine learning, and expand Railsense to improve rail safety on a global scale.

Built With

• arduino
• if-needed)-apis-&-integration:-rest-apis-for-communication-with-central-control-system-push-notifications-/-alert-apis-(to-notify-loco-pilot
• infrared-temperature-sensors-(j
• k-type
• matlab
• python
• sql
• station-master