Abstract | ||
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A mobile phone is getting smarter by employing a sensor and awareness of various contexts about a user and the terminal itself. In this paper, we deal with five storing positions of a smart phone on our body as a context: 1) front pocket of trousers, 2) back pocket of trousers, 3) jacket pocket (side), 4) chest pocket, and 5) around the neck (hanging). We propose a method for identifying the five positions with 29 features that characterize specific movements of a terminal at the position during walking. The result of offline experiment shows that an overall accuracy was 72.3% in a strict condition where datasets for a test were obtained from different people whose datasets were utilized for training a classifier. We also present a working prototype system with software framework for Android OS. An event of positional change is delivered to applications that conforms to APIs as well as to existing applications via preference settings. As a proof-of-concept application, a placement-aware heatstroke alerter was developed that tells a user about possible over (under) -estimate of the potential risk based on a storing position. |
Year | DOI | Venue |
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2012 | 10.1109/ICDCSW.2012.52 | ICDCS Workshops |
Keywords | Field | DocType |
on-body placement-aware smartphone,overall accuracy,chest pocket,offline experiment,different people,mobile phone,android os,smart phone,front pocket,jacket pocket,storing position,accuracy,dataset,software framework,api,mobile computing,classifier,sensor,accelerometers,android,heating | Mobile computing,Mobile radio,Android (operating system),Computer science,Accelerometer,Real-time computing,Mobile phone,Classifier (linguistics),Smart phone,Software framework | Conference |
Citations | PageRank | References |
5 | 0.52 | 11 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
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Kaori Fujinami | 1 | 316 | 41.25 |
Satoshi Kouchi | 2 | 22 | 1.80 |
Yuan Xue | 3 | 156 | 13.09 |