Automated surveillance is essential for the protection of Critical Infrastructures (CIs) in future
Smart Cities. The dynamic environments and bandwidth requirements demand systems that …

In smart city scenarios, the huge proliferation of monitoring cameras scattered in public
spaces has posed many challenges to network and processing infrastructure. A few dozen …

With recent advances in both AI and IoT capabilities, it is possible than ever to implement
surveillance systems that can automatically identify people who might represent a potential …

Recent advances in Deep Learning, have made possible distributed multi-camera vision
analytics targeted at a variety of surveillance applications involving automated real-time …

Trustworthy and real-time video surveillance aims to analyze the live camera streams in a
privacy-preserving manner for the decision-making of various advanced services, such as …

Sustainable smart city initiatives around the world have recently had great impact on the
lives of citizens and brought significant changes to society. More precisely, data-driven smart …

Edge computing efficiently extends the realm of information technology beyond the
boundary defined by cloud computing paradigm. Performing computation near the source …

Abstract Recent advances in Deep Learning have made possible distributed multi-camera
IoT vision analytics targeted at a variety of surveillance applications involving automated …

Internet-enabled cameras pervade daily life, generating a huge amount of data, but most of
the video they generate is transmitted over wires and analyzed offline with a human in the …

Driven by technological improvements, the noninvasive nature of cameras, affordable
prices, security concerns, and federal government grants to aid fighting terrorism, camera …