Raspberry Pi–Based Edge Vision System for Real-Time Optical Fault Detection in Smart Industrial IoT Networks
Elyor MuminovTashkent University of Information Technologies Named After Muhammad al-Khwarizmi,Tashkent,UzbekistanRaximjon AzimovAndijan State University,Andijan,UzbekistanAjay BadhanLovely Professional University,School of Computer Science and Engineering,Phagwara,IndiaHayotjon IsmatTashkent University of Information Technologies Named After Muhammad al-Khwarizmi,Tashkent,UzbekistanAmanpreet SinghSchool of Computer Applications Lovely Professional University,Phagwara,Punjab,India
2025
ABI
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The paper provides the design and analysis of an Edge Vision system (Raspberry Pi-based) to operate in realtime optical fault detection in Smart Industrial IoT Networks. The performance of automated systems can be significantly deteriorated by optical defects like misalignment, surface defects and obscured sensors. The system uses a Raspberry Pi 4 Model B, high resolution camera module and lightweight computer vision algorithms to do local inference at the edge to reduce latency and network bandwidth consumption. Careful hardware architecture, software workflow, circuit diagrams, and performance results are given.
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