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Privacy-Aware Smart Cameras: View Coverage via Socially Responsible Coordination

arXiv Security Archived Mar 25, 2026 ✓ Full text saved

arXiv:2603.23197v1 Announce Type: new Abstract: Coordination of view coverage via privacy-aware smart cameras is key to a more socially responsible urban intelligence. Rather than maximizing view coverage at any cost or over relying on expensive cryptographic techniques, we address how cameras can coordinate to legitimately monitor public spaces while excluding privacy-sensitive regions by design. This article proposes a decentralized framework in which interactive smart cameras coordinate to au

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    Computer Science > Cryptography and Security [Submitted on 24 Mar 2026] Privacy-Aware Smart Cameras: View Coverage via Socially Responsible Coordination Chuhao Qin, Lukas Esterle, Evangelos Pournaras Coordination of view coverage via privacy-aware smart cameras is key to a more socially responsible urban intelligence. Rather than maximizing view coverage at any cost or over relying on expensive cryptographic techniques, we address how cameras can coordinate to legitimately monitor public spaces while excluding privacy-sensitive regions by design. This article proposes a decentralized framework in which interactive smart cameras coordinate to autonomously select their orientation via collective learning, while eliminating privacy violations via soft and hard constraint satisfaction. The approach scales to hundreds up to thousands of cameras without any centralized control. Experimental evidence shows 18.42% higher coverage efficiency and 85.53% lower privacy violation than baselines and other state-of-the-art approaches. This significant advance further unravels practical guidelines for operators and policymakers: how the field of view, spatial placement, and budget of cameras operating by ethically-aligned artificial intelligence jointly influence coverage efficiency and privacy protection in large-scale and sensitive urban environments. Comments: This work has been submitted to the IEEE for possible publication Subjects: Cryptography and Security (cs.CR); Multiagent Systems (cs.MA); Systems and Control (eess.SY) Cite as: arXiv:2603.23197 [cs.CR]   (or arXiv:2603.23197v1 [cs.CR] for this version)   https://doi.org/10.48550/arXiv.2603.23197 Focus to learn more Submission history From: Chuhao Qin [view email] [v1] Tue, 24 Mar 2026 13:43:01 UTC (6,086 KB) Access Paper: HTML (experimental) view license Current browse context: cs.CR < prev   |   next > new | recent | 2026-03 Change to browse by: cs cs.MA cs.SY eess eess.SY References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
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    arXiv Security
    Category
    ◬ AI & Machine Learning
    Published
    Mar 25, 2026
    Archived
    Mar 25, 2026
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