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ARService: A Smartphone based Crowd-Sourced Data Collection and Activity Recognition Framework
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DOI：10.1016/j.procs.2018.04.142.png)
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Abstract
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In this paper, we present the ARService framework which is a crowd-sourced mobile sensing system with an online activity recognition module running on a smartphone. The system consists of a mobile application and a server part. The application logs data from sensors, particularly motion sensors, available on smartphones, data about the phone state, such as battery level, location information, as well as data from the wireless interfaces, such as the nearby access points. Besides being a data logger, the application also recognizes user activities, such as walking, sitting, using accelerometer in an online manner. On the server side, data is stored for further analysis and also visualized. ARService was continuosly used by 15 participants for a duration of one month in a data collection campaign. Besides the details of the framework, we present the online activity recognition performance and show that, up to 89% accuracy is achieved in recognizing the activities of the participants in an online manner. (C) 2018 The Authors. Published by Elsevier B.V.
Keywords:
Activity recognition
mobile sensors
performance analysis
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