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

Federated learning (FL) enables multiple worker devices share local models trained on their
private data to collaboratively train a machine learning model. However, local models are …

Cloud Computing and Cloud Platforms have become an essential resource for businesses,
due to their advanced capabilities, performance, and functionalities. Data redundancy …

Multi-access Edge Computing (MEC) enables mobile users to run various delay-sensitive
applications via offloading computation tasks to MEC servers. However, the location privacy …

A user's movement path can be precisely and concisely described as a concatenation of
straight lines having the user's turns as their end points. Learning such a path description or …

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 …

Indoor positioning has attracted considerable interest in both the industry and academic
communities because of its wide range of applications, such as asset tracking, healthcare …

Mobile-edge computing (MEC) raises the problem of selfish user devices that utilize less
computing resources than expected to execute offloading tasks or maliciously discard …

Owing to the ubiquity of wireless networks, WiFi fingerprinting is widely applied in indoor
localization. However, constructing a comprehensive radio map for WiFi indoor localization …

In this article, we study the problem of passive human localization using an infrared (IR)
thermal imaging camera which detects IR radiation emitted by human without carry-on …