Mobility monitoring in urban environments provides valuable insights into pedestrian and
vehicle movement. Understanding the causes and effects of changing mobility patterns can …

To fully exploit the capabilities of sensors in real life, especially cameras, smart camera
surveillance requires the cooperation from both domain experts in computer vision and …

The stop-and-go traffic pattern at urban intersections leads to excessive energy use due to
frequent vehicle braking, idling, and acceleration. This pattern, amplified by the growing use …

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 …

As the hardware cost decreases, more and more cameras have been deployed and used to
monitor traffics. Widely deployed cameras enable a wide range of computer vision-based …

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 …

Traffic surveillance is essential for regulating traffic and reducing congestion. Nonetheless,
the video data generated is non-structured, high-volume, bandwidth intensive and also …

Traffic monitoring systems are fundamental for making roads safer and more efficient. Newly
proposed traffic monitoring systems enable the use of IoT devices to monitor traffic in a cost …

This article presents an AI-enabled Smart Video Surveillance (SVS) designed to enhance
safety in community spaces such as educational and recreational areas, and small …

Complex inner-city junctions are among the most critical traffic areas for injury and fatal
accidents. The development of highly automated driving (HAD) systems struggles with the …