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

Quality control of sensing data poses a fundamental challenge in Spatial Crowdsourcing
(SC) applications, and various incentive mechanisms have been proposed to effectively …

This article proposes a new framework to model a scenario in which First Responders,
citizens, smart devices, or robots explore the environment in an emergency situation, ie, after …

With the continuous improvement of the sensing, transmission, storage, and computing
capabilities of mobile devices, they have become important tools for perceiving the physical …

With the development of the Industrial Internet of Things (IoT), the work of large-scale data
collection makes spatiotemporal crowdsensing (SC) play an important role. Mobile devices …

The emergence of vehicular crowdsensing (VCS) brings new opportunities and possibilities
for the collection of High-Definition (HD) maps. Unlike traditional mapping methods, VCS …

Mobile crowdsensing (MCS) utilizes the mobility of participating users and relies on the
sensing ability of user devices to complete high-quality sensing tasks with limited cost …

With the rapid development of the Internet of Things and the popularity of numerous sensing
devices, Mobile crowdsourcing (MCS) has become a paradigm for collecting sensing data …

Abstract Unlike crowdsourcing, Spatial Crowdsourcing (SC) requires workers to travel to a
specific physical location to accomplish a task. Due to its open concept, the platform accepts …

With the popularization of portable smart devices, the advance in ubiquitous connectivity
and the Internet of Things (IoT), mobile crowdsensing is becoming one of the promising …