Integrating environmental sensing and BLE-based location for improving daily activity recognition in OPH
Long Niu, Sachio Saiki, Masahide Nakamura · 2017
Recently, many studies about Activities of Daily Living (ADLs) recognition have been conducted, which can be applied to many real-life, human-centric problems such as eldercare and healthcare. In our previous work, we proposed an ADLs recognition system based on non-intrusive environment sensing for people in One-person Household (OPH). However, the proposed recognition system did not perform well, the micro-averaged and macro-averaged precision of most of the recognition models was only around 60%. In order to improve the quality of the system, in this article, we propose a new ADLs recognition system by integrating environment sensing and Bluetooth Low Energy (BLE) beacon technology and evaluate the new version of the ADLs recognition model by comparing the experimental data collected from a real resident in OPH.