TinyML for Empowering Low-Power IoT Edge Consumer Devices

IF 4.3 2区计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Consumer Electronics Pub Date : 2025-01-03 DOI:10.1109/TCE.2024.3482353

Rutvij H. Jhaveri;Hao Ran Chi;Huaming Wu

引用次数: 0

Abstract

Pervasive Artificial Intelligence (AI) has been promoted to be applicable to multiple services and markets, based on the recent surge in AI and machine learning (ML) techniques. Together with the fact that the market size of edge computing has been boosted to 16 billion USD last year (and a forecast to reach more than 200 billion USD by 2030), TinyML will be one of the main forces to embrace the new era of pervasive AI, by embedding the main operations (e.g., training, modeling, and others) in edge computing, relying on its relatively short physical distance to the users/end devices. Therefore, TinyML has promised to support ultra-low latency, enhanced security/privacy, highly demanded scalability, and potentially sustainability by reducing the frequency accessing centralized cloud computing.

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来源期刊

IEEE Transactions on Consumer Electronics 工程技术-电信学

CiteScore

7.70

自引率

9.30%

发文量

审稿时长

3.3 months

期刊介绍： The main focus for the IEEE Transactions on Consumer Electronics is the engineering and research aspects of the theory, design, construction, manufacture or end use of mass market electronics, systems, software and services for consumers.

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