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智能家居中人类活动识别系统的寿命。

The Lifespan of Human Activity Recognition Systems for Smart Homes.

机构信息

School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA 30308, USA.

出版信息

Sensors (Basel). 2023 Sep 7;23(18):7729. doi: 10.3390/s23187729.

Abstract

With the growing interest in smart home environments and in providing seamless interactions with various smart devices, robust and reliable human activity recognition (HAR) systems are becoming essential. Such systems provide automated assistance to residents or to longitudinally monitor their daily activities for health and well-being assessments, as well as for tracking (long-term) behavior changes. These systems thus contribute towards an understanding of the health and continued well-being of residents. Smart homes are personalized settings where residents engage in everyday activities in their very own idiosyncratic ways. In order to provide a fully functional HAR system that requires minimal supervision, we provide a systematic analysis and a technical definition of the lifespan of activity recognition systems for smart homes. Such a designed lifespan provides for the different phases of building the HAR system, where these different phases are motivated by an application scenario that is typically observed in the home setting. Through the aforementioned phases, we detail the technical solutions that are required to be developed for each phase such that it becomes possible to derive and continuously improve the HAR system through data-driven procedures. The detailed lifespan can be used as a framework for the design of state-of-the-art procedures corresponding to the different phases.

摘要

随着智能家居环境和提供与各种智能设备无缝交互的兴趣日益浓厚,强大可靠的人体活动识别 (HAR) 系统变得至关重要。这些系统为居民提供自动化帮助,或对其日常活动进行长期监测,以进行健康和幸福感评估,以及跟踪(长期)行为变化。因此,这些系统有助于了解居民的健康和持续幸福感。智能家居是个性化的环境,居民以他们自己独特的方式进行日常活动。为了提供一个需要最小监督的功能齐全的 HAR 系统,我们对智能家居的活动识别系统的生命周期进行了系统的分析和技术定义。这种设计的生命周期为 HAR 系统的不同阶段提供了保障,这些不同阶段是由家庭环境中常见的应用场景驱动的。通过上述阶段,我们详细介绍了每个阶段所需开发的技术解决方案,以便通过数据驱动的过程得出并不断改进 HAR 系统。详细的生命周期可用作对应不同阶段的最新流程设计的框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6bed/10536432/70c501c984bc/sensors-23-07729-g001.jpg

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