A Secure IoT-Based System for Real-Time Industrial Safety Monitoring in Hazardous Environments
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Keywords:
Industrial Safety Monitoring, Internet of Things (IoT), Real-Time Alert System, Hazard Detection, NodeMCU (ESP8266), Secure Data TransmissionAbstract
Industrial environments are prone to hazards like toxic gas leak, fire outbreak, extreme
temperature changes, etc., which can result in injuries to personnel, damaging equipment or stopping
production altogether. Traditional security systems are not able to provide real-time response, are not
scalable, and do not integrate with modern cloud-based operations analytics. Real time monitoring system
to monitor different Environmental hazards and keep the data secure with low cost using IoT. The next
proposed system is a weather station based on the architecture already having a proof of concept, using
microcontrollers like NodeMCUs, multi-modal sensors (gas, temperature, flame, and motion), and the
cloud such as ThingSpeak, Blynk for monitoring and alerting. The architecture also utilizes SSL
encryption, API-key-based authentication, and over-the-air updates to ensure data integrity and system
resilience. Use an experimental demonstration to show that it can quickly detect unsafe conditions and
notify people through mobile and web applications, so it can be used in factories, warehouses and
chemical plants. In this way, this work presented a secure, modular, and scalable framework to enrich the
area of occupational safety by using smart sensing, and real-time IoT communication.
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References
Kodali, R. K., & Mandal, S. (2016). IoT based weather station. Proceedings of the 2016 International Conference on Control, Instrumentation, Communication and Computational Technologies (ICCICCT), Kumaracoil, India, 680–683.
Nageswararao, J., & Murthy, G. K. (2017). Wireless weather monitor using Internet of Things. i-Manager’s Journal on Embedded Systems, 6(1), 30–36.
Devaraju, J. T. et al. (2015). Wireless portable microcontroller-based weather monitoring station, Measurement, vol. 76, pp. 189–200.
Baraki, P., Shastri, S., Mohammed, A., & Hegde, A. (2018). Real time weather analysis using ThingSpeak. International Journal of Pure and Applied Mathematics, 120(6), 661–682.
Munandar, A., et al. (2017). Design of real-time weather monitoring system based on mobile application using automatic weather station. Proceedings of the 2017 2nd International Conference on Automation, Cognitive Science, Optics, MEMS, and Information Technology (ICACOMIT), Jakarta, Indonesia, 44–47.
Malik, A. H., Parray, B. A., & Kohli, M. (2017). Smart city IoT based weather monitoring system. International Journal of Engineering and Computer Science, 7(5), 3–8.
NarasimhaRao, Y., Chandra, P. S., Revathi, V., &. Kumar, N. S, (2020). Providing enhanced security in IoT based smart weather system. Indones. J. Electr. Eng. Compute. Sci., vol. 18, no. 1, pp. 9–15.
Ali, Q. I. (2010). Design & implementation of a mobile phone charging system based on solar energy harvesting. Proceedings of the 1st International Conference on Energy, Power and Control (EPC-IQ01 2010), 264–267.
Ali, Q. I. (2016). "Enhanced power management scheme for embedded road side units." IET Computers & Digital Techniques, 10(4), 174-185. DOI: 10.1049/iet-cdt.2015.0123.
Ali, Q. I. (2012). "Design and implementation of an embedded intrusion detection system for wireless applications." IET Information Security, 6(3), 171-182. DOI: 10.1049/iet-ifs.2011.0152.
Ali, Q. I. (2016). "Securing solar energy‐harvesting road‐side unit using an embedded cooperative‐hybrid intrusion detection system." IET Information Security, 10(6), 386-402. DOI: 10.1049/iet-ifs.2015.0180.
Ali, Q. I. (2016). Green communication infrastructure for vehicular ad hoc network (VANET). Journal of Electrical Engineering, 16(2), 10-10.
Lazim Qaddoori, S., Ali, Q.I.: An embedded and intelligent anomaly power consumption detection system based on smart metering. IET Wirel. Sens. Syst. 13(2), 75–90
Merza, M.E., Hussein, S.H., Ali, Q.I., Identification scheme of false data injection attack based on deep learning algorithms for smart grids, Indonesian Journal of Electrical Engineering and Computer Science, 2023, 30(1), pp. 219–228, http://doi.org/10.11591/ijeecs.v30.i1.pp219-228
Alhabib M.H., Ali Q.I., (2023) . Internet of Autonomous Vehicles Communication Infrastructure: A Short Review, 24 (3),DOI: 10.29354/diag/168310
