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Edge Computing and Smart Data Processing in Ultrasound-Based Manufacturing
Abstract
Ultrasound-based manufacturing has emerged as a transformative technology, enabling precise, non-invasive, and efficient production processes across various industries such as automotive, aerospace, biomedical, and electronics. However, the real-time data generated by ultrasonic sensors presents significant challenges in terms of latency, bandwidth, and computational load when processed through traditional cloud-based systems. This chapter explores the integration of edge computing into ultrasound-based manufacturing, focusing on smart data processing strategies that bring computation closer to the data source. Edge devices are leveraged to perform initial data filtering, feature extraction, anomaly detection, and decision-making with minimal latency. We examine how this localized processing enhances the responsiveness, reliability, and security of ultrasound applications. Additionally, we delve into use cases, architectural frameworks, and future trends, including AI at the edge and federated learning. This convergence of edge computing and ultrasound-based manufacturing paves the way for intelligent, scalable, and sustainable industrial systems.
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