Edge AI Framework for Real-Time Device Diagnostics and Autonomous  Maintenance in Manufacturing and Healthcare

Ravi kiran gadiraju

Edge AI Framework for Real-Time Device Diagnostics and Autonomous Maintenance in Manufacturing and Healthcare

Authors

Ravi kiran gadiraju

Keywords:

Edge AI, Predictive Maintenance, Internet of Medical Things, Latency, Energy Efficiency, Real-Time Diagnostics

Abstract

The use of Edge Artificial Intelligence (AI) is revolutionizing the process of device diagnosticsand maintenance, as it allows analysis of devices in real-time on devices during manufacturingand healthcare facilities. In this paper, an Edge AI design is suggested, which integrates IoT sensors and on-device machine learning

References

Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge computing: Vision and challenges. IEEE Internet of Things Journal, 3(5), 637–646.

Lee, J., Bagheri, B., & Kao, H. A. (2015). A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18–23.

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Published

2023-08-15

How to Cite

Ravi kiran gadiraju. (2023). Edge AI Framework for Real-Time Device Diagnostics and Autonomous Maintenance in Manufacturing and Healthcare . Journal of Computational Analysis and Applications (JoCAAA), 31(3), 978–987. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5223