Human-centric sensing

M Srivastava, T Abdelzaher… - … Transactions of the …, 2012 - royalsocietypublishing.org
The first decade of the century witnessed a proliferation of devices with sensing and
communication capabilities in the possession of the average individual. Examples range …

Using mobile phones to determine transportation modes

S Reddy, M Mun, J Burke, D Estrin, M Hansen… - ACM Transactions on …, 2010 - dl.acm.org
As mobile phones advance in functionality and capability, they are being used for more than
just communication. Increasingly, these devices are being employed as instruments for …

CrowdRecruiter: Selecting participants for piggyback crowdsensing under probabilistic coverage constraint

D Zhang, H Xiong, L Wang, G Chen - Proceedings of the 2014 ACM …, 2014 - dl.acm.org
This paper proposes a novel participant selection framework, named CrowdRecruiter, for
mobile crowdsensing. CrowdRecruiter operates on top of energy-efficient Piggyback …

Recruitment framework for participatory sensing data collections

S Reddy, D Estrin, M Srivastava - … 2010, Helsinki, Finland, May 17-20 …, 2010 - Springer
Mobile phones have evolved from devices that are just used for voice and text
communication to platforms that are able to capture and transmit a range of data types …

Multi-task allocation in mobile crowd sensing with individual task quality assurance

J Wang, Y Wang, D Zhang, F Wang… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
Task allocation is a fundamental research issue in mobile crowd sensing. While earlier
research focused mainly on single tasks, recent studies have started to investigate multi-task …

Growing an organic indoor location system

J Park, B Charrow, D Curtis, J Battat, E Minkov… - Proceedings of the 8th …, 2010 - dl.acm.org
Most current methods for 802.11-based indoor localization depend on surveys conducted by
experts or skilled technicians. Some recent systems have incorporated surveying by users …

iCrowd: Near-Optimal Task Allocation for Piggyback Crowdsensing

H Xiong, D Zhang, G Chen, L Wang… - IEEE Transactions …, 2015 - ieeexplore.ieee.org
This paper first defines a novel spatial-temporal coverage metric, k-depth coverage, for
mobile crowdsensing (MCS) problems. This metric considers both the fraction of subareas …

Heterogeneous multi-task assignment in mobile crowdsensing using spatiotemporal correlation

L Wang, Z Yu, D Zhang, B Guo… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Mobile crowdsensing (MCS) is a new paradigm to collect sensing data and infer useful
knowledge over a vast area for numerous monitoring applications. In urban environments …

High quality participant recruitment in vehicle-based crowdsourcing using predictable mobility

Z He, J Cao, X Liu - 2015 IEEE Conference on Computer …, 2015 - ieeexplore.ieee.org
The potential of crowdsourcing for complex problem solving has been revealed by
smartphones. Nowadays, vehicles have also been increasingly adopted as participants in …

Sensloc: sensing everyday places and paths using less energy

DH Kim, Y Kim, D Estrin, MB Srivastava - … of the 8th acm conference on …, 2010 - dl.acm.org
Continuously understanding a user's location context in colloquial terms and the paths that
connect the locations unlocks many opportunities for emerging applications. While extensive …