We address the challenges in achieving optimal Quality of Information (QoI) for non-
dedicated vehicular Mobile Crowdsensing (MCS) systems, by utilizing vehicles not originally …

We study an intriguing and practical scenario of online Spatial Crowdsourcing (SC), in which
workers have the flexibility to perform tasks using various methods, such as walking, driving …

Edge-assisted mobile crowdsensing (EMCS) has gained significant attention as a data
collection paradigm. However, existing incentive mechanisms in EMCS systems rely on …

Urban challenges like air pollution, traffic congestion, and road quality demand precise and
timely detection for effective city monitoring. Traditional stationary sensors, costly with limited …

The ever-expanding volume of data in diverse domains necessitates effective methods for
selecting representative subsets while ensuring scalability. Submodular maximization, a …