AGENDA
9:00am - 9:30am: Registration
9:30am - 9:45am: Open Remark
9:45am - 10:30am: Keynote I: Mobile Health Data Crowdsourcing: Are We Ready For It?
Cecilia Mascolo, University of Cambridge, UK
10:30am - 11:15am: Session I: Application
- Quantifying Personal Exposure to Spatio-Temporally Distributed Air Pollutants using Mobile Sensors, Amanpreet Kaur: PEC University of Technology; Savina Singla: PEC University of Technology; Divya Bansal: PEC University of Technology
- Offloading Surrogates Characterization via Mobile Crowdsensing, Emanuel Lima: Instituto de Telecomunicações; Ana Aguiar: Instituto de Telecomunicações; Paulo Carvalho: Centro Algoritmi, Universidade do Minho
- Accurate and Low-cost Mobile Indoor Localization with 2-D Magnetic Fingerprints, Xirui Fan: Shanghai Jiao Tong University; Jing Wu: Shanghai Jiao Tong University; Chengnian Long: Shanghai Jiao Tong University; Yanmin Zhu: Shanghai Jiao Tong University
11:15am - 11:30am: Coffee Break
11:30am - 12:15pm: Keynote II: The current state of indoor mapping
Michael Peter, University of Twente, Netherland
12:15pm - 1:00pm: Session II: Design & Systems
- Mew: A Plug-n-Play Framework for Task Allocation in Mobile Crowdsensing, Garvita Bajaj: Indraprastha Institute of Information Technology, Delhi; Pushpendra Singh: Indraprastha Institute of Information Technology, Delhi
- Design Strategies for Efficient Access to Mobile Device Users via Amazon Mechanical Turk, Jason Jacques: University of Cambridge; Per Ola Kristensson: University of Cambridge
- Who to Query? Spatially-Blind Participatory Crowdsensing under Budget Constraints, Mai Elsherief: University of Califor3ia, Santa Barbara; Morgan Vigil-Hayes: University of California, Santa Barbara; Ramya Raghavendra: IBM Research; Elizabeth Belding: University of California, Santa Barbara
1:00pm - 2:00pm: Lunch
2:00pm - 2:45pm: Keynote III: Crowdsourced positioning systems: research challenges and applications
Niki Trigoni, University of Oxford, UK
2:45pm - 3:30pm: Session III: Data Quality
- Extracting Mobility Demand from Crowdsourced Location Traces, JoÜo Rodrigues: IT Porto; JoÜo Pereira: IT Porto; Ana Aguiar: FEUP
- Detecting Location Fraud in Indoor Mobile Crowdsensing, Qiang Xu: McMaster University; Rong Zheng: McMaster University; Ezzeldin Tahoun: McMaster University
- Integrity of Data in a Mobile Crowdsensing Campaign: A Case Study, Heng Zhang: Purdue University; Saurabh Bagchi: Purdue University; He Wang: Purdue University (Video Presentation)
3:30pm - 3:45pm: Coffee Break
3:45pm - 4:30pm: Session IV: Security & Privacy
- SPICE: Secure Proximity-based Infrastructure for Close Encounters, Aarathi Prasad: Skidmore College; Xiaohui Liang: UMass Boston; David Kotz: Dartmouth College
- A Privacy Preserving Mobile Crowdsensing Architecture for a Smart Farming Application, Lars Huning: University of Osnabrück, Institute of Computer Science; Jan Bauer: University of Osnabrück, Institute of Computer Science; Nils Aschenbruck: University of Osnabrück, Institute of Computer Science
- VeriNet: Passcode-Preserving User Verification on Smartwatches via Behavior Biometrics, Xiaoxuan Lu: University of Oxford; Bowen Du: University of Warwick; Xuan Kan: Tongji University; Hongkai Wen: University of Warwic, Andrew Markham: University of Oxford; Niki Trigoni: University of Oxford
4:30pm - 5:15pm: Panel discussion: Killer Apps and Research Challenges