In MCS (mobile crowd sensing), reducing network overhead, protecting IoT user privacy and
increasing the participation enthusiasm of perception task are key issues. The QLPPIA (an …

The crowdsourcing scheme emerges as a promising solution for data-based application in
the Internet of Things (IoT) network by dividing the large-scale complex sensing tasks into …

Crowdsourcing is a novel distributed problem-solving mechanism that can provide the
collection and share of marine data in the Internet of Things for the smart ocean …

Data privacy leakage can be severe when a malicious Internet of Things (IoT) node sends
requests to gather private data from an edge-computing-based IoT cloud storage system …

With the rapid digitalization of various industries, mobile crowdsensing (MCS), an intelligent
data collection and processing paradigm of the industrial Internet of Things, has provided a …

The mobile crowdsensing (MCS) technology with a large number of Internet of Things (IoT)
devices provides an economic and efficient solution to participation in coordinated large …

Mobile crowdsensing (MCS) has gained popularity for its potential to leverage individual
mobile devices to sense, collect, and analyze data instead of deploying sensors. As the …

With the popular use of IoT devices, edge computing has been widely applied in the Internet
of things (IoT) and regarded as a promising solution for its wide distribution, decentralization …

Mobile-edge crowdsensing is capable of providing a large amount of data via pervasive
mobile terminals for Industrial Internet of Things (IIoT). However, the generated data often …

In developing smart city, the growing popularity of machine learning (ML) that appreciates
high-quality training data sets generated from diverse Internet-of-Things (IoT) devices raises …