Resident activity recognition based on binary infrared sensors and soft computing
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ORIGINAL ARTICLE
Resident activity recognition based on binary infrared sensors and soft computing Qiangfu Zhao1 · Chia‑Ming Tsai2 · Rung‑Ching Chen2 · Chung‑Yi Huang2
Received: 27 January 2016 / Accepted: 11 August 2017 © Springer-Verlag GmbH Germany 2017
Abstract The basic concept of a smart space (SS) is to be aware of the context information related to environmental and human behavioral changes, and to provide appropriate services accordingly. To obtain context information, we may use video cameras, microphones, and other monitoring devices. Although these devices can obtain complex environmental data, they are not suitable for building private smart space (PSS) because of the privacy issue. Human users do not like being monitored in their private spaces. In this study, we investigate the possibility of recognizing certain activities using binary data collected by using infrared sensors. Infrared sensors have been used mainly for detecting the existence/absence of the residents in a region of interest. Here, we consider four types of activities, namely, NoActivity, Very-Weak-Activity, Weak-Activity, and StrongActivity. Our main goal is to provide a way for building PSS using low-cost and non-privacy-sensitive devices. We have conducted some primary experiments by collecting user activity information using binary infrared sensors. Generally speaking, activity related sensor data are sensitive to various factors. To effectively address this issue, we propose a recognition method based on fuzzy decision tree. The results of the primary experiments show that the recognition rate of proposed method can be as high as 85.49%. The results are encouraging, and show the possibility of building PSS using binary infrared sensors. * Rung‑Ching Chen [email protected] 1
School of Computer Science and Engineering, The University of Aizu, Tsuruga, Ikkimachi, Aizu‑Wakamatsu, Fukushima 965‑8580, Japan
Department of Information Management, Chaoyang University of Technology, 168, Jifeng E. Rd., Wufeng District, 41349 Taichung, Taiwan, ROC
2
Keywords Activity type recognition · Fuzzy logic · Fuzzy decision tree · Private smart space · Non-privacysensitive smart space
1 Introduction Smart space (SS), such as a smart office or smart home, is an integrated computing application. An SS equipped with many sensing devices can understand the needs of the residents and provide appropriate services. To build an SS, we may use cameras and/or microphones to monitor the region of interest (ROI). However, monitoring devices like cameras and microphones are not suitable for building private smart space (PSS) because they are privacy-sensitive. To avoid this problem, we may use simple sensors like infrared sensors, temperature sensors, illuminance sensors [14], or wearable devices [11]. These simple sensors are low-cost and non-privacy-sensitive, and can be easily deployed in various places in the ROI. On the other hand, the data provided by the simple sensors are usually less informative. To build a PSS using simple sensors, sp
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