Yu Chen

By Deeraj Nagothu, Nihal Poredi and Yu Chen

Intelligent surveillance systems play an essential role in modern smart cities to enable situational awareness. As part of the critical infrastructure, surveillance systems are often targeted by attackers aiming to compromise the security and safety of smart cities. Manipulating the audio or video channels could create a false perception of captured events and bypass detection. This chapter presents an overview of the attack vectors designed to compromise intelligent surveillance systems and discusses existing detection techniques. With advanced machine learning (ML) models and computing resources, both attack vectors and detection techniques have evolved to use ML-based techniques more effectively, resulting in non-equilibrium dynamics. The current detection techniques vary from training a neural network to detect forgery artifacts to use the intrinsic and extrinsic environmental fingerprints for any manipulations. Therefore, studying the effectiveness of different detection techniques and their reliability against the defined attack vectors is a priority to secure the system and create a plan of action against potential threats.

Part of the book: Intelligent Video Surveillance

By Qian Qu, Han Sun and Yu Chen

Smart Home improves the quality of our life in various aspects such as the convenience of managing our home, efficiency of energy consumption, and secure living environments. Taking advantage of the Internet of Medical Things (IoMT), smart homes in the context of healthcare have attracted a lot of attention to provide a more convenient, easier accessible, and personalized healthcare experience. Leveraging state-of-the-art techniques like Digital Twins (DT), machine learning (ML) algorithms, and human action recognition (HAR), Smart Healthcare at Home (SHAH) not only provides independent healthcare service options and social support but also gives seniors or other individuals who are in need a reliable way for real-time monitoring and safety preservation. This chapter will provide a comprehensive overview of the technical components of a SHAH paradigm, which is based on an architecture that integrates DT, IoMT, and artificial intelligence (AI) technology. The design rationales and key function blocks are illustrated in detail. In addition, taking seniors’ safety monitoring as a case study, a prototype of a SHAH system is experimentally investigated, and the performance and design tradeoffs are highlighted. Finally, this chapter also provides an overview of this exciting field’s existing challenges and opportunities.

Part of the book: Internet of Things