Target localization refers to identifying a target location based on sensory data readings
gathered by sensing agents (robots, UAVs), surveying a certain area of interest. Existing …

The evolution of the Internet of Things (IoT) has empowered modern industries with the
capability to implement large-scale IoT ecosystems, such as the Industrial Internet of Things …

Smart environmental monitoring has gained prominence, where target localization is of
utmost importance. Employing UAVs for localization tasks is appealing owing to their low …

Internet of things (IoT) is a key enabler for target localization, where IoT-based sensors work
towards identifying target's location in an area of interest (AoI). Appropriate selection of IoT …

This paper addresses the issue of tracking a mobile target, through a data-driven active
sensor selection mechanism in the Internet of Things (IoT) sensing applications. IoT …

In target localization applications, readings from multiple sensing agents are processed to
identify a target location. The localization systems using stationary sensors use data fusion …

The use of Internet of Things (IoT) in environment monitoring has led to the development of
Smart Environmental Monitoring (SEM) paradigm. Target or source localization, that …

Abstract Deep Reinforcement Learning (DRL) has emerged as a powerful paradigm for
solving complex problems. However, its full potential remains inaccessible to a broader …

Mobile Crowdsensing (MCS), an important component of the Internet of Things (IoT), is a
paradigm which utilizes people carrying smart devices, referred to as “workers”, to perform …

Workers recruitment remains a significant issue in Mobile Crowdsourcing (MCS), where the
aim is to recruit a group of workers that maximizes the expected Quality of Service (QoS) …