This paper presents a disruptive approach" Immersive Networking" enabling massively
distributed IoT nodes to participate in autonomous and cooperative decision-making. The …

The Internet of Things (IoT) is made up of software components and physical objects that are
deeply intertwined, each operating on different spatial and temporal scales, exhibiting …

The use of IoT has become pervasive and IoT devices are common in many domains.
Industrial IoT (IIoT) utilises IoT devices and sensors to monitor machines and environments …

IoT applications are increasingly employing machine learning (ML) algorithms to manage
and control the operational environment autonomously while predicting future actions. To …

The massive increase of IoT devices and their collected data raises the question of how to
analyze all that data. Edge computing provides a suitable compromise, but the question …

Large-scale IoT applications based on machine learning (ML) demand both edge and cloud
processing for, respectively, AI inference and ML training tasks. Context-aware applications …

As the number of interconnected devices increases and more artificial intelligence (AI)
applications upon the Internet of Things (IoT) start to flourish, so does the environmental cost …

Abstract The Internet of Things (IoT) consists of heterogeneous devices such as wearables
and monitoring devices that collect data to provide autonomous decision-making and smart …

Edge computing plays a critical role in the Internet of Things (IoT) environment as it
potentially supports the time-critical IoT applications' resources as well as latency …

As the Internet of Things (IoT) continues to burgeon, the demand for intelligent processing at
the network's edge becomes increasingly imperative. This research paper delves into the …