2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC) | 2021
A Multi-case Perspective Analytical Framework for Discovering Human Daily Behavior from Sensors using Process Mining
Abstract
Due to the rapid development of sensor technology, wearable sensors have been widely applied in various real-life human applications and improved the mass adoption of smart environments. This recent technology offers a pioneering opportunity to recognize human daily behavior patterns from a large amount of collected data. In this work, we address the challenge of applying process mining to discover human daily behavior patterns from sensors. Sensor data could be seen as the execution of a process representing user daily activity. However, it requires additional tasks for investigating the perspective of sensor data that comes from diverse environmental settings. Therefore, we propose an analytical framework to discover human daily behavior patterns from various sensors in a smart environment. In order to evaluate the proposed framework, a real-world dataset in a smart environment is used. From the conducted experiment, this framework could be used to transform general human activity data and takes into account the process mining to discover human daily behavior in accordance with a multi-case perspective process model (i.e., user-based, time-based, and sensor flow pattern).