MUMBAI, India, Sept. 22 -- Intellectual Property India has published a patent application (202641110586 A) filed by Vallurupalli Nageswara Rao Vignana Jyothi Institute Of Engineering And Technology on September 15, 2026, for A Smart Iot-Based Boiler Monitoring System Using Raspberry Pi For Real-Time Smoke Detection And Efficiency Prediction.
Inventor includes Mrs. Y. Prasanthi.
The application for the patent was published on September 18, 2026, under issue no. 38/2026.
Abstract: ABSTRACT [0018] A real-time boiler efficiency monitoring system is disclosed that employs computer vision and a compact object-detection model to evaluate combustion quality from exhaust smoke. Live video frames of the boiler stack are processed by a YOLOv8 Nano network previously trained on a publicly available smoke dataset. The model localizes smoke regions and estimates their density; when the detected density exceeds a predefined efficiency threshold the system issues an instantaneous alert. The entire pipeline runs on a resource-constrained edge device, eliminating the need for invasive sensors or high-end computing hardware. Continuous visual monitoring thereby supplies plant personnel with timely indications of incomplete combustion, fuel wastage or potential equipment malfunction while supporting predictive maintenance and environmental compliance. This project presents a real-time boiler efficiency monitoring system using OpenCV and a YOLOv8 Nano deep learning model. Traditional methods for assessing boiler performance are often invasive, costly, and lack real-time responsiveness. In this approach, live video footage of boiler exhaust is analyzed using computer vision to detect the presence and density of smoke—an indicator of combustion inefficiency. The YOLOv8 Nano model, trained on the SMOKE100 dataset via Roboflow, enables fast and accurate smoke detection, even on resource-constrained devices. An efficiency threshold is predefined, and when smoke detection crosses this limit, the system triggers instant alerts, allowing for timely corrective actions. This non- invasive, lightweight, and cost-effective solution offers continuous monitoring, supports predictive maintenance, and ensures boilers operate within optimal efficiency standards, contributing to safer and more sustainable industrial operations.
Disclaimer: Curated by HT Syndication.
