Understanding Ethics, Privacy, and Regulations in Smart Video Surveillance for Public Safety
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Abstract (arXiv)
Recently, Smart Video Surveillance (SVS) systems have been receiving more attention among scholars and developers as a substitute for the current passive surveillance systems. These systems are used to make the policing and monitoring systems more efficient and improve public safety. However, the nature of these systems in monitoring the public's daily activities brings different ethical challenges. There are different approaches for addressing privacy issues in implementing the SVS. In this paper, we are focusing on the role of design considering ethical and privacy challenges in SVS. Reviewing four policy protection regulations that generate an overview of best practices for privacy protection, we argue that ethical and privacy concerns could be addressed through four lenses: algorithm, system, model, and data. As an case study, we describe our proposed system and illustrate how our system can create a baseline for designing a privacy perseverance system to deliver safety to society. We used several Artificial Intelligence algorithms, such as object detection, single and multi camera re-identification, action recognition, and anomaly detection, to provide a basic functional system. We also use cloud-native services to implement a smartphone application in order to deliver the outputs to the end users.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 15 of its 40 references that are in the map. First posted on arXiv 25 Dec 2022.
Builds on
15 of 40 references.
References · 15
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3 more
Built on by
Citing papers per year: 2023: 3; 2024: 1; 2025: 3.
7 papers.
- 2023Understanding the Challenges and Opportunities of Pose-based Anomaly Detectioncited by 14
- 2023Understanding Policy and Technical Aspects of AI-Enabled Smart Video Surveillance to Address Public Safetycited by 9
- 2024Towards Adaptive Human-centric Video Anomaly Detection: A Comprehensive Framework and A New Benchmarkcited by 6
- 2025Shopformer: Transformer-Based Framework for Detecting Shoplifting via Human Posecited by 6
- 2025A Survey on Video Anomaly Detection via Deep Learning: Human, Vehicle, and Environmentcited by 4
- 2023Real-World Community-in-the-Loop Smart Video Surveillance -- A Case Study at a Community Collegecited by 1
- 2025TRACER: Efficient Object Re-Identification in Networked Cameras through Adaptive Query Processingcited by 0
- 2025A Survey on Video Anomaly Detection via Deep Learning: Human, Vehicle, and Environment19 Aug 2025
- 2025TRACER: Efficient Object Re-Identification in Networked Cameras through Adaptive Query Processing13 Jul 2025
- 2025Shopformer: Transformer-Based Framework for Detecting Shoplifting via Human Pose28 Apr 2025
- 2024Towards Adaptive Human-centric Video Anomaly Detection: A Comprehensive Framework and A New Benchmark26 Aug 2024
- 2023Real-World Community-in-the-Loop Smart Video Surveillance -- A Case Study at a Community College22 Mar 2023
- 2023Understanding the Challenges and Opportunities of Pose-based Anomaly Detection9 Mar 2023
- 2023Understanding Policy and Technical Aspects of AI-Enabled Smart Video Surveillance to Address Public Safety8 Feb 2023