基于家庭自动化数据的行为漂移检测的量化指标
Quantitative Indicators for Behaviour Drift Detection from Home Automation Data.
作者信息
Veronese Fabio, Masciadri Andrea, Comai Sara, Matteucci Matteo, Salice Fabio
机构信息
Department of Electronics, Information and Bioengineering, Politecnico di Milano - via Anzani 42, 22100, Como, Italy.
出版信息
Stud Health Technol Inform. 2017;242:208-215.
PMID:28873801
Abstract
Smart Homes diffusion provides an opportunity to implement elderly monitoring, extending seniors' independence and avoiding unnecessary assistance costs. Information concerning the inhabitant behaviour is contained in home automation data, and can be extracted by means of quantitative indicators. The application of such approach proves it can evidence behaviour changes.
摘要
智能家居的普及为实施老年人监测提供了契机，可增强老年人的独立性并避免不必要的护理成本。居民行为信息包含在家庭自动化数据中，可通过量化指标提取。这种方法的应用证明它能够发现行为变化。
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