A Review on Suspicious Behavior Detection at Heritage Sites Using Quantum Enhanced Deep Learning

Heritage sites are significant historical and cultural locations that draw tourists from all over the world. Heritage sites and tourism coexist in a complicated and mutually beneficial way. Exploring heritage sites, such as ancient monuments, historic buildings, and cultural landmarks, are valuable treasures that connect us to our past. Suspicious behavior refers to actions, conduct, or activities that appear out of the ordinary or raise concerns about potential wrongdoing or harm. Suspicious behavior at these sites, such as vandalism, theft, or violence, has a harmful impact. These actions damage the sites and our collective heritage, make visitors feel unsafe, and can put people's safety at risk. Protecting and preserving heritage sites is crucial to ensure that they can continue to educate and inspire people for generations to come. Suspicious behavior detection at heritage sites involves a multifaceted approach. It includes trained security personnel, surveillance cameras, access control, bag checks, and vigilant crowd management. These methods aim to safeguard the site's cultural and historical significance by identifying and addressing any potential threats or unauthorized activities effectively. In this paper, we will furthermore discuss heritage sites, suspicious behavior and detection techniques using deep learning and victims of these issues.