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Alok Kumar,
Vedprakash Singh,
Alok Prasad,
Atul Kumar Yadav,
Satyam Kumar,
- Assistant Professor,, Department of Electrical Engineering Bansal Institute of Engineering and Technology Lucknow,, Uttar Pradesh, India
- Student, Department of Electrical Engineering Bansal Institute of Engineering and Technology Lucknow,, Uttar Pradesh, India
- Student, Department of Electrical Engineering Bansal Institute of Engineering and Technology Lucknow,, Uttar Pradesh, India
- Quality Engineer, Department of Electrical Engineering Bansal Institute of Engineering and Technology Lucknow,, Uttar Pradesh, India
- Student, Department of Electrical Engineering Bansal Institute of Engineering and Technology Lucknow,, Uttar Pradesh, India
Abstract
The high incidence of accidents at railway level crossings due to human errors and lack of proactive track monitoring is a challenge for rail safety in high-density networks. This paper proposes the development and validation of an intelligent automated railway crossing system- IARCS that leverages sensor fusion and IoT communication to eliminate human dependency and mitigate intrusion risks. The core system deploys an Arduino Uno for the purpose of primary gate control, incorporating Ultrasonic Sensors HC-SR04 for precise train approach and departure detection, and a dedicated Passive Infrared PIR Sensor for robust, real-time intrusion monitoring within the crossing zone after the gates are closed. Upon the detection of any trapped obstacle (human or vehicle), a secondary ESP32 microcontroller is activated. The major contribution of this system is its double-layered warning mechanism. Locally, it initiates visual LED and audible Buzzer warnings. Most importantly, it utilizes the ESP32 to establish a low-latency alert path (via LoRa/Wi-Fi and a WhatsApp/Telegram Bot Service) for sending an immediate hazard notification directly to the Locomotive Pilot’s smartphone. The implementation plan, based on a Finite State Machine (FSM) control logic, ensures failsafe and predictable gate operation via a Servo Motor. Performance validation focuses on maximizing detection accuracy and minimizing alert latency, demonstrating that the IARCS offers a reliable, cost-effective, and proactive solution to significantly enhance operational safety and prevent collisions at level crossings.
Keywords: Railway Safety, Level Crossing Automation, Intrusion Detection, IoT (Internet of Things), Arduino Uno, ESP32, PIR Sensor, Ultrasonic Sensor, Real-time Alerting, Smart Transportation, Embedded Systems.
Alok Kumar, Vedprakash Singh, Alok Prasad, Atul Kumar Yadav, Satyam Kumar. Intelligent automated railway crossing gate control system. Journal of Microcontroller Engineering and Applications. 2026; 13(01):-.
Alok Kumar, Vedprakash Singh, Alok Prasad, Atul Kumar Yadav, Satyam Kumar. Intelligent automated railway crossing gate control system. Journal of Microcontroller Engineering and Applications. 2026; 13(01):-. Available from: https://journals.stmjournals.com/jomea/article=2026/view=238928
References
- Semtech L. LoRaWAN: A technical overview. Semtech Corporation, December. 2019.
- Jiao J, Wang X, Han C, Quan H, Zhao J. Robust Indoor Localization in Dynamic Environments: A Multi- source Unsupervised Domain Adaptation Framework. IEEE Internet of Things Journal. 2025 Jun 25.
- Jain V. Convergence of IoT, Blockchain, and Computational Intelligence in Smart Cities. Kumar R, Yie LW, Teyarachakul S, editors. CRC Press, Taylor & Francis Group; 2024.
- Siddiqui HU, Saleem AA, Raza MA, Zafar K, Munir K, Dudley S. IoT based railway track faults detection and localization using acoustic analysis. IEEE Access. 2022 Sep 27;10:106520-33.
- Khonina SN, Kazanskiy NL, Oseledets IV, Khabibullin RM, Nikonorov AV. Eyes of the Future: Decoding the World Through Machine Vision. Technologies. 2025 Nov 7;13(11):507.
- Basha, S. M., et al. (2021). Smart railway gate control system using Raspberry Pi and IoT. Journal of Physics: Conference Series, 1916(1), 012158.
- Augustin A, Yi J, Clausen T, Townsley WM. A study of LoRa: Long range & low power networks for the internet of things. Sensors. 2016 Sep 9;16(9):1466.
- Sathiyanarayanan, M., & Sivaraman, K. (2018). Vision-based obstacle detection for unmanned railway level crossing using deep learning. In 2018 International Conference on Communication and Signal Processing (ICCSP) (pp. 0731-0735).
- Alahi ME, Sukkuea A, Tina FW, Nag A, Kurdthongmee W, Suwannarat K, Mukhopadhyay SC. Integration of IoT-enabled technologies and artificial intelligence (AI) for smart city scenario: recent advancements and future trends. Sensors. 2023 May 30;23(11):5206.
- Sharma S, Verma VK. An integrated exploration on internet of things and wireless sensor networks. Wireless Personal Communications. 2022 Jun;124(3):2735-70.
- Kolban N. Kolban’s Book on ESP32. leanpub. com. April 1st. 2018.
- Bayram M. 12th INTERNATIONAL CONFERENCE ON APPLIED ANALYSIS AND MATHEMATICAL MODELING (ICAAMM24) Abstract Book, July 19-23, 2024, Istanbul-Turkey.
- Loránd S. LISTA LUCRĂRILOR CITATE. InInternational Conference on Electrical Machines (ICEM) 1992 (Vol. 2, pp. 697-701).
- Rehman SU. Beyond the Classroom. Wearable Devices and Smart Technology for Educational Teaching Assistance. 2024 Dec 24:331.
- Paterson J, Aldabbagh A. Gesture- controlled robotic arm utilizing OpenCV. In2021 3rd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) 2021 Jun 11 (pp. 1-6). IEEE.
- Shiferaw AY, Esakki B, Pari T, Elumalai E, Mobayen S, Bartoszewicz A. Design and implementation of morphed multi-rotor vehicles with real-time obstacle detection and sensing system. Sensors. 2021 Sep 15;21(18):6192.

Journal of Microcontroller Engineering and Applications
| Volume | 13 |
| 01 | |
| Received | 03/12/2025 |
| Accepted | 08/12/2025 |
| Published | 20/03/2026 |
| Publication Time | 107 Days |
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