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Pbn: Towards practical activity recognition using smartphone-based body sensor networks
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| Venue: | In Proc. of Sensys ’11 |
| Citations: | 30 - 4 self |
BibTeX
@INPROCEEDINGS{Keally_pbn:towards,
author = {Matthew Keally and Jianxin Wu and Gang Zhou and Andrew Pyles and Guoliang Xing},
title = {Pbn: Towards practical activity recognition using smartphone-based body sensor networks},
booktitle = {In Proc. of Sensys ’11},
year = {}
}
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Abstract
Thevastarrayofsmallwirelesssensorsisaboontobody sensornetworkapplications,especiallyinthecontextawareness and activity recognition arena. However, most activity recognition deployments and applications are challenged to provide personal control and practical functionality for everyday use. We argue that activity recognition for mobile devices must meet several goals in order to provide a practical solution: user friendlyhardwareandsoftware,accurate and efficient classification, and reduced reliance on ground truth. To meet these challenges, we present PBN: Practical Body Networking. Through the unification of TinyOS motes and Android smartphones, we combine the sensing power of on-bodywireless sensors with the additionalsensing power, computationalresources, and user-friendlyinterfaceof anAndroidsmartphone. We provideanaccurateand efficientclassificationapproachthroughtheuseofensemble learning. We explore the propertiesof different sensors and sensor data to further improve classification efficiency and reducerelianceon user annotatedgroundtruth. We evaluate our PBN system with multiple subjectsoveratwo week periodanddemonstratethatthesystemiseasytouse,accurate, andappropriateformobiledevices. Categories andSubject Descriptors C.3 [Special-Purpose and Application-Based Sys-
Keyphrases
smartphone-based body sensor network towards practical activity recognition everyday use android smartphones user friendlyhardwareandsoftware sensor data on-bodywireless sensor efficient classification tinyos mote practical solution several goal user-friendlyinterfaceof anandroidsmartphone pbn system mobile device ground truth activity recognition arena classification efficiency reduced reliance practical functionality application-based sys personal control activity recognition deployment propertiesof different sensor multiple subjectsoveratwo week practical body networking activity recognition
