Abstract In recent times, Mobile Crowdsensing (MCS) has garnered considerable attention
and emerged as a promising sensing paradigm. The MCS approach leverages the …

Smartphone-based indoor localization has attracted considerable attentions in both
research and industrial areas. However, the localization accuracy and robustness are still …

With the recent surge in autonomous driving vehicles, the need for accurate vehicle
detection and tracking is critical now more than ever. Detecting vehicles from visual sensors …

For years, vehicle trajectory data have increasingly been important for a wide range of
applications, from driver behavior investigation/classification, travel time/distance estimation …

Sparse mobile crowdsensing is a practical paradigm for large sensing systems, which
recruits a small number of users to sense data from only a few subareas and, then, infers the …

Localization is one of the most important topics of cyber physical system. In the last decades,
much attention has been paid to the precise localization and performance evaluation in …

Although crowdsensing has emerged as a popular information collection paradigm, its
security and privacy vulnerabilities have come to the forefront in recent years. However, one …

Detecting passive attacks is always considered difficult in vehicular networks. Passive
attackers can eavesdrop on the wireless medium to collect beacons. These beacons can be …

In opportunistic mobile crowdsensing, participants (workers) accept to carry out the
requested sensing tasks only if they are already close to or within the regions of interest …

Due to the pervasiveness of geomagnetic fields and independence from external
infrastructure, localization with smartphone-based magnetic has attracted considerable …