Advanced Video & Image Processing Algorithms for Enhancing Predictive Maintenance in IoT – Enabled Smart Infrastructure

Author(s)	Akshat Bhutiani
Country	United States
Abstract	The integration of predictive maintenance algorithms into IoT enabled smart infrastructure has revolutionized asset management by enhancing operational efficiency, reducing downtime, and lowering maintenance costs. This paper explores advanced video and image processing algorithms tailored to address unique challenges of predictive maintenance in smart infrastructure systems. By leveraging techniques such as object detection, anomaly recognition, and pattern analysis, these algorithms enable the accurate monitoring of critical components like energy systems, HVAC units and industrial machinery. The proposed solutions incorporate state-of-the-art imagine processing frameworks, including convolutional neural networks (CNNs) and optical flow analysis, optimized for deployment on edge devices to ensure real-time analysis and minimal latency. Experimental results validated on diverse IoT datasets, demonstrate significant improvements in fault detection accuracy and system improvements.
Keywords	Predictive maintenance, IoT enhanced smart infrastructure, video processing algorithms, image processing algorithms, fault detection, anomaly recognition
Field	Engineering
Published In	Volume 5, Issue 6, November-December 2023
Published On	2023-11-09
DOI	https://doi.org/10.36948/ijfmr.2023.v05i06.22346
Short DOI	https://doi.org/g82h4j

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International Journal For Multidisciplinary Research