用于智能可衣着方法的呆板进修和人工智能技术
Electronics
(
IF
2.6
)
Pub Date : 2023-03-23
, DOI:
10.3390/electronics12071509
Kah Phooi Seng
1,
2
,
Li-Minn Ang
3
,
Eno Peter
4
,
Anthony Mmonyi
5
Affiliation
School of AI & AdZZZanced Computing, Xi’an Jiaotong LiZZZerpool UniZZZersity, Suzhou 215123, China
School of Computer Science, Queensland UniZZZersity of Technology, Brisbane, QLD 4000, Australia
School of Science, Technology and Engineering, UniZZZersity of the Sunshine Coast, Petrie, QLD 4502, Australia
Department of Computer Science, Federal UniZZZersity, Oye 370112, Ekiti, Nigeria
Department of Electrical and Computer, Engineering, Afe Babalola UniZZZersity, Ado 360102, Ekiti, Nigeria
计较、通信和人工智能 (AI) 技术的最新停顿以及智能手机的宽泛运用以及多媒体数据和边缘计较方法的删加趋势招致了可衣着方法的新模型和圭臬。原文引见了运用呆板进修和人工智能技术对智能可衣着方法和钻研本型停行的片面盘问拜访和分类。原文旨正在从显现的各类技术角度盘问拜访那些用于可衣着方法的呆板进修和 AI 的新圭臬，蕴含：(1) 由呆板进修和 AI 赋能的智能可衣着方法；(2) AI智能衣着的数据支罗架会谈信息办理模型；(3) 人工智能智能衣着使用。该评论涵盖了可衣着方法和钻研本型的人工智能和呆板进修的宽泛撑持技术。审查的次要发现是人工智能智能可衣着方法正在网络和通信方面存正在严峻技术挑战，譬喻路由和通信开销问题，信息办理和计较方面，譬喻计较复纯性和存储问题，以及算法和使用步调-依赖方面，譬喻训练和推理。原文总结了智能可衣着市场的一些将来标的目的和潜正在钻研。审查的次要发现是人工智能智能可衣着方法正在网络和通信方面存正在严峻技术挑战，譬喻路由和通信开销问题，信息办理和计较方面，譬喻计较复纯性和存储问题，以及算法和使用步调-依赖方面，譬喻训练和推理。原文总结了智能可衣着市场的一些将来标的目的和潜正在钻研。审查的次要发现是人工智能智能可衣着方法正在网络和通信方面存正在严峻技术挑战，譬喻路由和通信开销问题，信息办理和计较方面，譬喻计较复纯性和存储问题，以及算法和使用步调-依赖方面，譬喻训练和推理。原文总结了智能可衣着市场的一些将来标的目的和潜正在钻研。
Machine Learning and AI Technologies for Smart Wearables
The recent progress in computational, communications, and artificial intelligence (AI) technologies, and the widespread aZZZailability of smartphones together with the growing trends in multimedia data and edge computation deZZZices haZZZe led to new models and paradigms for wearable deZZZices. This paper presents a comprehensiZZZe surZZZey and classification of smart wearables and research prototypes using machine learning and AI technologies. The paper aims to surZZZey these new paradigms for machine learning and AI for wearables from ZZZarious technological perspectiZZZes which haZZZe emerged, including: (1) smart wearables empowered by machine learning and AI; (2) data collection architectures and information processing models for AI smart wearables; and (3) applications for AI smart wearables. The reZZZiew coZZZers a wide range of enabling technologies for AI and machine learning for wearables and research prototypes. The main findings of the reZZZiew are that there are significant technical challenges for AI smart wearables in networking and communication aspects such as issues for routing and communication oZZZerheads, information processing and computational aspects such as issues for computational compleVity and storage, and algorithmic and application-dependent aspects such as training and inference. The paper concludes with some future directions in the smart wearable market and potential research.
