Human activity recognition (HAR) is a rapidly growing field that utilizes smart devices, sensors, and algorithms to automatically classify and identify the actions of individuals within a given environment. These systems have a wide range of applications, including assisting with caring tasks, increasing security, and improving energy efficiency. However, there are several challenges that must be addressed in order to effectively utilize HAR systems in multi-resident environments. One of the key challenges is accurately associating sensor observations with the identities of the individuals involved, which can be particularly difficult when residents are engaging in complex and collaborative activities. This paper provides a brief overview of the design and implementation of HAR systems, including a summary of the various data collection devices and approaches used for human activity identification. It also reviews previous research on the use of these systems in multi-resident environments and offers conclusions on the current state of the art in the field.

翻译：人类活动识别（HAR）是一个快速发展的领域，它利用智能设备、传感器和算法自动分类和识别特定环境中个体的行为。这些系统具有广泛的应用场景，包括辅助护理任务、增强安全性以及提高能效。然而，在多住户环境中有效部署HAR系统仍需解决若干挑战。其中一个关键问题在于准确关联传感器观测结果与相关个体的身份，尤其是在住户参与复杂协作活动时尤为困难。本文简要概述了HAR系统的设计与实现，总结了用于人类活动识别的多样化数据采集设备与方法，并回顾了此前在多住户环境中应用这些系统的研究成果，最后对该领域的技术发展现状进行了总结。