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智能生活服务与应用中的人体行为识别:上下文感知、数据可用性、个性化和隐私。

Human Action Recognition in Smart Living Services and Applications: Context Awareness, Data Availability, Personalization, and Privacy.

机构信息

National Research Council of Italy, Institute for Microelectronics and Microsystems, 73100 Lecce, Italy.

出版信息

Sensors (Basel). 2023 Jun 29;23(13):6040. doi: 10.3390/s23136040.

DOI:10.3390/s23136040
PMID:37447889
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10346639/
Abstract

Smart living, an increasingly prominent concept, entails incorporating sophisticated technologies in homes and urban environments to elevate the quality of life for citizens. A critical success factor for smart living services and applications, from energy management to healthcare and transportation, is the efficacy of human action recognition (HAR). HAR, rooted in computer vision, seeks to identify human actions and activities using visual data and various sensor modalities. This paper extensively reviews the literature on HAR in smart living services and applications, amalgamating key contributions and challenges while providing insights into future research directions. The review delves into the essential aspects of smart living, the state of the art in HAR, and the potential societal implications of this technology. Moreover, the paper meticulously examines the primary application sectors in smart living that stand to gain from HAR, such as smart homes, smart healthcare, and smart cities. By underscoring the significance of the four dimensions of context awareness, data availability, personalization, and privacy in HAR, this paper offers a comprehensive resource for researchers and practitioners striving to advance smart living services and applications. The methodology for this literature review involved conducting targeted Scopus queries to ensure a comprehensive coverage of relevant publications in the field. Efforts have been made to thoroughly evaluate the existing literature, identify research gaps, and propose future research directions. The comparative advantages of this review lie in its comprehensive coverage of the dimensions essential for smart living services and applications, addressing the limitations of previous reviews and offering valuable insights for researchers and practitioners in the field.

摘要

智能生活是一个日益突出的概念,它涉及将先进技术融入家庭和城市环境中,以提高公民的生活质量。从能源管理到医疗保健和交通等各个领域的智能生活服务和应用的一个关键成功因素是人类动作识别 (HAR) 的效果。HAR 根植于计算机视觉,旨在使用视觉数据和各种传感器模式来识别人类动作和活动。本文对智能生活服务和应用中的 HAR 文献进行了广泛的回顾,综合了主要贡献和挑战,同时为未来的研究方向提供了见解。该综述深入探讨了智能生活的基本方面、HAR 的现状以及这项技术对社会的潜在影响。此外,本文还详细研究了智能生活中受益于 HAR 的主要应用领域,如智能家居、智能医疗和智能城市。通过强调上下文感知、数据可用性、个性化和隐私这四个维度在 HAR 中的重要性,本文为寻求推进智能生活服务和应用的研究人员和从业者提供了全面的资源。本文献综述采用了有针对性的 Scopus 查询方法,以确保涵盖该领域相关出版物的全面性。努力对现有文献进行了彻底评估,确定了研究差距,并提出了未来的研究方向。本综述的比较优势在于其对智能生活服务和应用至关重要的各个维度的全面覆盖,解决了以前综述的局限性,并为该领域的研究人员和从业者提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e9/10346639/9a07a0c71219/sensors-23-06040-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e9/10346639/ebfe9ad61c2e/sensors-23-06040-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e9/10346639/5eb3499f56c2/sensors-23-06040-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e9/10346639/9a07a0c71219/sensors-23-06040-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e9/10346639/ebfe9ad61c2e/sensors-23-06040-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e9/10346639/5eb3499f56c2/sensors-23-06040-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2e9/10346639/9a07a0c71219/sensors-23-06040-g003.jpg

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Sensors (Basel). 2023 Jan 17;23(3):1083. doi: 10.3390/s23031083.
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4
Generisch-Net: A Generic Deep Model for Analyzing Human Motion with Wearable Sensors in the Internet of Health Things.通用网络:一种用于在健康物联网中分析人类运动的通用深度模型。
Sensors (Basel). 2024 Sep 24;24(19):6167. doi: 10.3390/s24196167.
5
A Multi-Agent System for Service Provisioning in an Internet-of-Things Smart Space Based on User Preferences.一种基于用户偏好的物联网智能空间中服务供应的多智能体系统。
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随机森林的纵向数据分析综述。
Brief Bioinform. 2023 Mar 19;24(2). doi: 10.1093/bib/bbad002.
4
STC-NLSTMNet: An Improved Human Activity Recognition Method Using Convolutional Neural Network with NLSTM from WiFi CSI.STC-NLSTMNet:一种基于 WiFi CSI 的卷积神经网络与 NLSTM 改进的人体活动识别方法。
Sensors (Basel). 2022 Dec 29;23(1):356. doi: 10.3390/s23010356.
5
Adaptation, personalization and capacity in mental health treatments: a balancing act?心理健康治疗中的适应、个性化和能力:一种平衡行为?
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6
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7
Human Activity Recognition: Review, Taxonomy and Open Challenges.人体活动识别:综述、分类与开放挑战。
Sensors (Basel). 2022 Aug 27;22(17):6463. doi: 10.3390/s22176463.
8
The State-of-the-Art Sensing Techniques in Human Activity Recognition: A Survey.人体活动识别中的最新传感技术:综述。
Sensors (Basel). 2022 Jun 17;22(12):4596. doi: 10.3390/s22124596.
9
Human Action Recognition From Various Data Modalities: A Review.基于多种数据模态的人类行为识别综述
IEEE Trans Pattern Anal Mach Intell. 2023 Mar;45(3):3200-3225. doi: 10.1109/TPAMI.2022.3183112. Epub 2023 Feb 3.
10
Framework for Simultaneous Indoor Localization, Mapping, and Human Activity Recognition in Ambient Assisted Living Scenarios.在智能家居场景中实现同时进行室内定位、建图和人体活动识别的框架。
Sensors (Basel). 2022 Apr 28;22(9):3364. doi: 10.3390/s22093364.