With the advancement in communication techniques and sensor technologies, mobile
crowdsensing (MCS)—one of the most successful applications of crowdsourcing—has …

Quality improvement methods are essential to gathering high-quality crowdsourced data,
both for research and industry applications. A popular and broadly applicable method is task …

Privacy-preserving online multi-task assignment is a crucial aspect of spatial crowdsensing
on untrusted platforms, where multiple real-time tasks are allocated to appropriate workers …

Road safety, optimized traffic management, and passenger comfort have always been the
primary goals of the vehicle networking research community. Advances in computer and …

In mobile crowdsensing, location-based task recommendation requires each data requester
to submit a task-related geometric range to crowdsensing service providers such that they …

Smart grids (SG) are electricity grids that communicate with each other, provide reliable
information, and enable administrators to operate energy supplies across the country …

In this paper, we investigate the incentive problem in Spatial Crowdsourcing (SC), where
mobile social-aware workers have unknown qualities and can share their answers to tasks …

In this paper, we present a comprehensive, in-depth survey of the literature on reinforcement
learning approaches to decision optimization problems in a typical ridesharing system …

Crowdsensed Data Trading (CDT) is a novel data trading paradigm, in which each data
consumer can publicize its data demand as some crowdsensing tasks, and some mobile …

There has been a dramatic growth of shared mobility applications such as ride-sharing, food
delivery, and crowdsourced parcel delivery. Shared mobility refers to transportation services …