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Analysis Study Research Paper | Information Technology | United States of America | Volume 10 Issue 1, January 2021 | Popularity: 4.7 / 10
Edge AI for Real - Time Health Monitoring using Streaming Data
Nithin Reddy Desani, Rajashekhar Reddy Kethi Reddy
Abstract: The advent of Edge AI has transformed the landscape of real - time health monitoring by enabling local data processing and immediate decision - making at the source of data generation. This paper explores the application of Edge AI in health monitoring, discussing its architecture, benefits, challenges, and future directions. Through a comprehensive review of existing systems and technologies, we aim to provide insights into the integration of AI at the edge for enhancing patient care and health outcomes. Edge AI significantly reduces latency, enhances data privacy, and increases the scalability and reliability of health monitoring systems. By processing data locally on wearable devices and IoT sensors, Edge AI allows for real - time analysis and immediate feedback, which is crucial for managing chronic diseases, monitoring vital signs, and responding to health emergencies. This paper also delves into the practical applications of Edge AI in various healthcare scenarios, presenting case studies and coding examples to illustrate its potential and effectiveness. Furthermore, we address the challenges related to computational constraints, energy consumption, and model updates on edge devices, and propose solutions to overcome these hurdles. Ultimately, this paper seeks to provide a comprehensive understanding of how Edge AI can revolutionize healthcare by enabling smarter, faster, and more secure health monitoring systems.
Keywords: Edge AI, Real - Time Health Monitoring, IoT, Wearable Devices, Data Processing, Healthcare, Machine Learning, Privacy, Latency, Scalability
Edition: Volume 10 Issue 1, January 2021
Pages: 1669 - 1674
DOI: https://www.doi.org/10.21275/ES21116104333
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