International Journal of Science, Engineering and TechnologyAuthors: Ashwini Vinod Waghale, Dr. K. P. Yadav, Dr. Salim A. Chavan
Abstract: There are several types of threats to human safety and industry that include gas leakage, excess temperature, vibration, fire, and machinery malfunction. This literature review aims at assessing the role of Internet of Things (IoT), Machine Learning (ML), and Edge Computing techniques in real-time industrial threat detection and monitoring. The literature review evaluates the use of multi-sensor system, machine learning for classification, Raspberry Pi based edge computing, MQTT communication protocol, and web-based monitoring systems. This paper focuses on Random Forest based classification of hazards, real-time monitoring of sensors, AES-256 Encryption-Decryption, authentication, secure MQTT communication, Flask dashboard, alert generation and relay based machine shutdown techniques. This paper discusses some of the challenges that include lack of real time validation, use of static data, sensor variations, secure data transfer, and combination of intelligent predictions with safety response mechanism. There is scope for future research in areas of secure IoT communication, edge based machine learning, real-time data processing, encryption and industrial safety response mechanism.
DOI: https://zenodo.org/records/22975804
