Spatial crowdsourcing (SC) is an emerging paradigm of crowdsourcing, which commits
workers to move to some particular locations to perform spatio-temporal-relevant tasks (eg …

Mobile CrowdSensing (MCS) is an emerging paradigm in the distributed acquisition of smart
city and Internet of Things (IoT) data. MCS requires large number of users to enable access …

Incentive plays an important role in knowledge discovery, as it impels users to provide high-
quality knowledge. To promise incentive schemes with transparency, blockchain technology …

Mobile crowdsensing has emerged as a popular platform to solve many challenging
problems by utilizing users' wisdom and resources. Due to user diversity, the data provided …

In this paper, we focus on the incentive mechanism design for a vehicle-based,
nondeterministic crowdsensing system. In this crowdsensing system, vehicles move along …

Incentive mechanisms are essential for stimulating adequate worker participation to achieve
good truth discovery performance in mobile crowdsensing (MCS) systems. However, most of …

Data quality, or sometimes referred to as data credibility, is a critical issue in mobile crowd
sensing (MCS) and more generally Internet of Things (IoT). While candidate solutions, such …

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 …

Mobile crowd sensing is a new paradigm that enables smart mobile devices to collect and
share various types of sensing data in urban environments. However, new challenges arise …

Geomagnetism has recently attracted considerable attention for indoor localization due to its
pervasiveness and independence from extra infrastructure. Its location signature has been …