Fault Detection and Diagnosis of Cyber-Physical System Using the Computer Vision and Image Processing

In the techno world, Corporate Business applies new technologies for manufacturing and production with numerous cyber-physical system strategies. This makes the process depend upon multiple computers, machines, and applications with varying specifications, efficiency, and latency. These technological strategies are extremely diverse on cyber-physical systems, from an extensive range of processing technologies is available. The currently available technologies are not well adapted to these processes, which require information management regarding fault detection and diagnosis at a complexity level separated from technology. In this article, the Image Processing assisted Computer Vision Technology for Fault Detection System (IM-CVFD) is suggested to resolve such issues in industrial cyber-physical systems. Group Activation Mapping Algorithm is presented for efficient information collection from the processed output, simplifying the managing of fault details with different needs. Besides achieving the optimized information concerning latency, efficiency, the Uncertainty Reduction algorithm is introduced. In a suitable processing environment, a detailed simulation is conducted. The empirical findings indicate the high efficiency of the IM-CVFDwitha with a minimum error rate, energy usage, and minimized delay with high service. In contrast with conventional methods, the IM-CVFD obtains a better result efficiently.