Crowdsensing has received widespread attention in recent years. It is extensively employed
in smart cities and intelligent transportation systems. This paper comprehensively surveys …

Crowdsourcing has led to a paradigm shift in how commercial houses execute projects by
lowering the production cost. A crucial aspect of crowdsourcing is selecting the best set of …

Collaborative mobile crowdsourcing (CMCS) allows entities, eg, local authorities or
individuals, to hire a team of workers from the crowd of connected people, to execute …

Mobile crowdsourcing (MC) is an effective way of engaging large groups of smart devices to
perform tasks remotely while exploiting their built-in features. It has drawn great attention in …

Mobile crowdsourcing (MCS) is a promising way to monitor urban-scale data by leveraging
the crowds' power and has attracted much attention recently. How to recruit suitable workers …

Internet-of-Things (IoT) networks intelligently connect thousands of physical entities to
provide various services for the community. It is witnessing an exponential expansion, which …

In mobile crowd sensing (MCS), complex tasks often require collaboration among multiple
workers with diverse expertise and sensors. However, few studies consider the sensing time …

Allocating tasks to the best-fit candidates is a classical problem in crowdsourcing (CS). Most
of the existing approaches assume that the task and candidate knowledge is known in …

Mobile crowd sourcing (MCS) enables a distributed problem-solving model in which a crowd
of smart devices' users is engaged in the task of solving a data sensing problem through an …

Collaborative crowdsensing (CCS) requires the recruited team to collaborate closely to
complete sensing tasks with high quality of service (QoS). The team recruitment of CCS is …