Safety is the most important requirement for autonomous vehicles; hence, the ultimate
challenge of designing an edge computing ecosystem for autonomous vehicles is to deliver …

The Internet of Vehicles (IoV) is an emerging paradigm that is driven by recent
advancements in vehicular communications and networking. Meanwhile, the capability and …

In the last five years, edge computing has attracted tremendous attention from industry and
academia due to its promise to reduce latency, save bandwidth, improve availability, and …

Distributed edge intelligence is a disruptive research area that enables the execution of
machine learning and deep learning (ML/DL) algorithms close to where data are generated …

Over the past century, vehicles have predominantly functioned as a means of transportation.
However, as vehicular computation and communication capacities continue to expand, it is …

Sensing data plays a pivotal role in connected and autonomous vehicles (CAVs), enabling
CAV to perceive surroundings. For example, malicious applications might tamper this life …

Autonomous mobile robots (AMRs) have been widely utilized in industry to execute various
on-board computer-vision applications including autonomous guidance, security patrol …

In the last 5 years, with the vast improvements in computing technologies, eg, sensors,
computer vision, machine learning, and hardware acceleration, and the wide deployment of …

Connected and Autonomous Vehicles (CAVs) is becoming more and more popular for
automobile academic and industry community. Communication mechanisms play an …

Autonomous mobile robots (AMRs) have the capability to execute a wide range of tasks with
minimal human intervention. However, one of the major limitations of AMRs is their limited …