People
- Professor Klara Nahrstedt: Principle Investigator
- Haiming Jin: Ph.D. candidate
Timeline
- Fall 2014-Spring 2017
Project Description
This project is a part of the Tustworthy Health & Wellness (THaW) project, which is an NSF-funded project that tackles many of the research challenges to provide trustworthy information systems for health and wellness.
Recent years have witnessed the emergence of mobile crowd sensing (MCS) systems, which leverage the public crowd equipped with various mobile devices for large scale sensing tasks. Such MCS systems also obtain their recent popularity in the domain of mobile healthcare. For example, in the US FDA advocated MCS system, MedWatcher, designed for post-market medical device surveillance, users upload photos about their medical devices to the MedWatcher server to help identify visible problems with their devices. Another example is the MyHeartMap Challenge, which utilizes user-provided photos to construct a map of AED devices across the city.
However, one fundamental problem with these MCS systems is that there lack incentive mechanisms that can effectively stimulate user participation. Hence, this project aims to design incentive mechanisms for MCS systems.
Publications
- Haiming Jin, Lu Su, Houping Xiao, Klara Nahrstedt, “INCEPTION: Incentivizing Privacy-preserving Data Aggregation for Mobile Crowd Sensing Systems“, the 17th ACM Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc 2016), Paderborn, Germany, July 2016
- Haiming Jin, Lu Su, Bolin Ding, Klara Nahrstedt, Nikita Borisov, “Enabling Privacy-Preserving Incentives for Mobile Crowd Sensing Systems“, the 36th International Conference on Distributed Computing Systems (ICDCS 2016), Nara, Japan, June 2016
- Haiming Jin, Lu Su, Danyang Chen, Klara Nahrstedt, Jinhui Xu, “Quality of Information Aware Incentive Mechanisms for Mobile Crowd Sensing Systems“, the 16th ACM Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc 2015), Hangzhou, China, June 2015
Funding Agencies
This project is supported by the a collaborative award from the National Science Foundation (NSF award numbers CNS-1329686, 1329737,1330142 and 1330491).