Abstract Advanced Machine Learning (ML) algorithms can be applied using Edge
Computing (EC) to detect anomalies, which is the basis of Artificial Intelligence of Things …

The Industrial Internet of Things (IIoT) ecosystem faces increased risks and vulnerabilities
due to adopting Industry 4.0 standards. Integrating data from various places and converging …

This study addresses anomaly detection in smart city environments driven by the Internet of
Things. In these cities, digital interconnection and the extensive network of sensors generate …

Video Surveillance Systems (VSSs) are used in a wide range of applications including
public safety and perimeter security. They are deployed in places such as markets …

The increase in the deployment of surveillance camera in outdoor and indoor settings have
resulted in a growing demand for intelligent systems that can accurately detect and …

In recent years, the concept of smart cities has garnered increasing attention as urban areas
grapple with the challenges of population growth, resource management, and infrastructure …

In the context of escalating safety concerns across various domains, the tasks of Video
Anomaly Detection (VAD) and Video Anomaly Recognition (VAR) have emerged as critically …

The integration of machine learning (ML), blockchain, and the Internet of Things (IoT) in
smart cities represents a pivotal advancement in urban innovation. This convergence …

Nowadays there is growing demand for surveillance applications due to the safety and
security from anomalous events. An anomaly in the video is referred to as an event that has …

The study of human behaviors aims to gain a deeper perception of stimuli that control
decision making. To describe, explain, predict, and control behavior, human behavior can …