Unleashing the Power of the Crowd: Towards Efficient and Sustainable Mobile Crowdsensing
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School of Science |
Doctoral thesis (article-based)
| Defence date: 2017-06-09
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Authors
Date
2017
Major/Subject
Mcode
Degree programme
Language
en
Pages
66 + app. 57
Series
Aalto University publication series DOCTORAL DISSERTATIONS, 96/2017
Abstract
Mobile crowdsensing has become a popular computing paradigm. It enables ubiquitous mobile devices, including wearable and industrial equipment, to collect and share sensing data at large scales. The crowdsourced data is analyzed comprehensively to understand phenomena of common interest or to create sensor-enriched maps. Examples include the monitoring of city-scale traffic, the sharing of discount information in shopping malls, and so on. This thesis explores challenges associated with efficiently bootstrapping and continuously improving the performance of mobile crowdsensing systems with crowdsourced data. The research questions include exploring the feasibility of adopting crowdsourced data to create new services, creating algorithms for the efficient collecting, organizing and utilizing crowdsourced data, and offering reliable services during the bootstrap stage while keep improving the service quality afterwards. In particular, we try to obtain answers from the practice of designing and developing two real-life mobile crowdsensing systems: one uses cellular signal-strength traces contributed by mobile users to achieve mobile energy efficiency; another adopts crowdsourced images and inertial sensor readings to offer indoor location-based services.Description
Supervising professor
Ylä-Jääski, Antti, Prof., Aalto University, Department of Computer Science, FinlandThesis advisor
Xiao, Yu, Prof., Aalto University, Department of Communications and Networking, FinlandKeywords
mobile crowdsensing, mobile energy efficiency, indoor navigation
Other note
Parts
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[Publication 1]: Zhonghong Ou, Jiang Dong, Shichao Dong, JunWu, Antti Ylä-Jääski, Pan Hui, Ren Wang, Alexander W. Min. Utilize Signal Traces From Others? A Crowdsourcing Perspective of Energy Saving in Cellular Data Communication. IEEE Transactions on Mobile Computing, vol.14, no.1, pages 194-207, Jan. 2015.
DOI: 10.1109/TMC.2014.2316517 View at publisher
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[Publication 2]: Jiang Dong, Yu Xiao, Zhonghong Ou, Antti Ylä-Jääski. Utilizing internet photos for indoor mapping and localization – opportunities and challenges. In The First International Workshop on Smart Cities and Urban Informatics in conjunction with IEEE INFOCOM 2015 (SmartCity 2015), Hong Kong, pages 636-641, Apr. 2015.
DOI: 10.1109/INFCOMW.2015.7179457 View at publisher
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[Publication 3]: Jiang Dong, Yu Xiao, Marius Noreikis, Zhonghong Ou, Antti Ylä-Jääski. iMoon: Using Smartphones for Image-based Indoor Navigation. In The 13th ACM Conference on Embedded Networked Sensor Systems (SenSys ’15), Seoul, pages 85-97, Nov. 2015.
DOI: 10.1145/2809695.2809722 View at publisher
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[Publication 4]: Jiang Dong, Yu Xiao, Zhonghong Ou, Yong Cui, Antti Ylä-Jääski. Indoor Tracking using Crowdsourced Maps. In The 15th International Conference on Information Processing in Sensor Networks (IPSN ’16), Vienna, pages 1-6, Apr. 2016.
DOI: 10.1109/IPSN.2016.7460679 View at publisher
- [Publication 5]: Jiang Dong, Yu Xiao, Marius Noreikis, Yong Cui, Antti Ylä-Jääski. Exploiting Mobile Crowdsensing for Creating Indoor Navigation Maps. Aalto University publication series SCIENCE+TECHNOLOGY Aalto-ST 3/2017, pages 1-9, 2017.