With the installation of enormous public safety and transportation infrastructure cameras,
video analytics has come to play an essential part in public safety. Typically, video analytics …

Edge-side real-time video analytics systems recognize spatial or temporal events (eg,
vehicle counting) in a video stream. To meet the delay requirement, existing systems in …

Smart city applications are revolutionizing the way people interact with diverse systems in
city-wide applications. Internet of Things (IoT) and machine learning are two enabling …

The ever-increasing number of Internet of Things (IoT) devices has created a new computing
paradigm, called edge computing, where most of the computations are performed at the …

Sending data to the cloud for analysis was a prominent trend during the past decades,
driving cloud computing as a dominant computing paradigm. However, the dramatically …

The number of cameras deployed to the edge of the network increases by the day, while
emerging use cases, such as smart cities or autonomous driving, also grow to expect …

Recently, edge computing has received considerable attention as a promising solution to
provide deep learning-based video analysis services in real-time. However, due to the …

Edge computing is a relatively recent phenomenon in the computing world, which takes
cloud computing services closer to the end user and is distinguished by fast processing and …

The advancements and progress in artificial intelligence (AI) and machine learning, and the
numerous availabilities of mobile devices and Internet technologies together with the …

Breakthroughs in deep learning, GPUs, and edge computing have paved the way for always-
on, live video analytics. However, to achieve real-time performance, a GPU needs to be …