Advanced International Journal of Multidisciplinary Research

E-ISSN: 2584-0487 •   Impact Factor: 9.11

An Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Multimodal Real-time Fatigue and Heat Risk Detection System for Industrial Machines using Thermal-visual Image Fusion and AI-based Assessment

Author(s) L. Bala Gangamma, T. Kaveri, V. Ahalya, H. Mounika, S. Mounika
Country India
Abstract Industrial machines are important in the contemporary factory setup, and as machinery is overutilized, it may end up overheating and mechanical exhaustion, thus raising the chances of machinery breakages and accidents. The traditional methods of monitoring, e.g. the manual inspection, which is done periodically or the use of just one specific type of sensor, are usually slow, inefficient, and can be easily distorted. In an attempt to overcome this shortcoming, this project brings to use an intelligent real-time surveillance system which incorporates the use of thermal and visual imaging. The thermal camera follows the changes in temperature in order to identify some abnormal heat distribution whereas the visual camera records surface and structural patterns related to wear and fatigue. Combining data of the two cameras using image fusion techniques, they will have better diagnostics output which is more informative and more precise. The analysis is done with deep learning models such as MobileNetV3 and ResNet-50 which can be computed with high precision and have lightweight computation. It is a fast, cost-effective, convenient solution, which means that the suggested system is appropriate when it should be implemented in factories in real-time, when it is used in the outside, and when the environment can be quite dangerous. It will be able to detect problems at an initial state and prevent equipment failures, reduce downtime, and increase the safety of the workplace.
Keywords MobileNetV3, ResNet-50, Heat risk detection.
Discipline Engineering
Published In Volume 4, Issue 2, March-April 2026
Published On 2026-04-04
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