IMT Atlantique Engineer School, 29238 Brest, France.
Delta Dore Company, 35270 Bonnemain, France.
Sensors (Basel). 2021 Sep 9;21(18):6037. doi: 10.3390/s21186037.
Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of sensors have encouraged the development of smart environments, such as smart homes. Smart homes can offer home assistance services to improve the quality of life, autonomy, and health of their residents, especially for the elderly and dependent. To provide such services, a smart home must be able to understand the daily activities of its residents. Techniques for recognizing human activity in smart homes are advancing daily. However, new challenges are emerging every day. In this paper, we present recent algorithms, works, challenges, and taxonomy of the field of human activity recognition in a smart home through ambient sensors. Moreover, since activity recognition in smart homes is a young field, we raise specific problems, as well as missing and needed contributions. However, we also propose directions, research opportunities, and solutions to accelerate advances in this field.
物联网 (IoT) 技术的最新进展和传感器成本的降低，鼓励了智能环境的发展，例如智能家居。智能家居可以提供家庭辅助服务，以提高居民的生活质量、自主性和健康水平，特别是对于老年人和依赖者。为了提供这些服务，智能家居必须能够理解居民的日常活动。用于识别智能家居中人类活动的技术每天都在进步。然而，新的挑战每天都在出现。在本文中，我们通过环境传感器介绍了智能家居中人类活动识别领域的最新算法、工作、挑战和分类法。此外，由于智能家居中的活动识别是一个年轻的领域，我们提出了具体的问题，以及缺失和需要的贡献。然而，我们还提出了方向、研究机会和解决方案，以加速该领域的进展。
