MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202641093599 A) filed by Dr. S. A. Sahaaya Arul Mary; Dr. Poongodi C; Dr. Arul V; and Dr. Logeswaran K on August 02, 2026, for Explainable Machine Learning-Based Iot Architecture For Industrial Safety Monitoring.
Inventors include Dr. S. A. Sahaaya Arul Mary; Dr. Poongodi C; Dr. Arul V; and Dr. Logeswaran K.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: The present system discloses an Explainable Machine Learning-Based IoT Architecture for Industrial Safety Monitoring that integrates heterogeneous Industrial IoT sensors, edge computing, explainable artificial intelligence, and cloud analytics to enable proactive hazard detection in industrial environments. The system continuously acquires environmental, electrical, mechanical, and worker safety data, performs preprocessing at the edge, predicts hazardous events using explainable machine learning algorithms, and generates human-interpretable explanations through SHAP, LIME, or equivalent explainability techniques. A dynamic risk assessment module evaluates hazard severity and recommends corrective actions while simultaneously issuing real-time alerts via cloud-based communication services. The proposed architecture enhances transparency, operator trust, regulatory compliance, and industrial safety by combining predictive intelligence with interpretable decision support, making it suitable for smart factories, manufacturing plants, chemical industries, oil and gas facilities, mining operations, and other Industry 4.0 applications.
Disclaimer: Curated by HT Syndication.
