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Author: search.filters.author.Akroum, HamzaSubject: search.filters.subject.Artificial Intelligence of Things

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    Leveraging AIoT for advanced quality control in production lines
    (Institute of Electrical and Electronics Engineers Inc, 2023) Hiou, Mohamed Yanis; Akroum, Hamza
    Nowadays, edge computing has emerged as a crucial component in the fourth industrial revolution, effectively merging data processing in close proximity to its source. This approach not only enhances the efficiency of data processing but also integrates data acquisition, analysis capabilities, sensing, and communication. Additionally, the Internet of Things (IoT) holds substantial importance within Industry 4.0, serving as a fundamental technology for wireless connectivity, data collection, and real-time monitoring. Simultaneously, while edge computing offers numerous advantages, it also presents challenges such as security concerns, data-intensive services, handling incomplete data, and notably, substantial investment and maintenance costs. To address these issues, cloud computing technology emerges as the optimal solution. This article aims to to propose an innovative approach called Artificial Intelligence of Things (AIoT) for optimizing production management. The focus of this project is the development of a production line for quality control capable of classifying gears as well as detecting defective ones. The production line collects comprehensive data, which is subsequently transmitted to a server for further processing. The results are then displayed through various interfaces, including an a web dashboard, A desktop interface and an Android app, providing analytics insights. This project leverages the integration of AI and IoT technologies within the AIoT framework to create a fully autonomous environment that significantly enhances overall efficiency.