Weighing mainstream and alternative accounts…
Ambient surveillance is quietly turning everyday places into data-rich control zones.
Ambient surveillance describes a shift from isolated observation toward pervasive, networked sensing. In this account, cameras, phones, smart objects, and other sensors collect environmental data and use computational analysis to recognize patterns, interpret images, and adapt services or security systems. The defining feature is not one particular device, but surveillance becoming distributed through ordinary environments.
Source mix
4 of 6 institutional
Smart objects turn daily life into a sensor. The quiet danger is that opting out starts to look like leaving society.
A phone, camera, or smart device can record more than a single encounter. Networked systems combine those traces to infer where people go, what they do, and what they prefer. The convenience is visible. The data trail is not. When ordinary spaces become digital enclosures, participation itself can start demanding a surrender of privacy.
Featured · Analysis · blog.uehiro.ox.ac.uk
Ambient Intelligence | Practical Ethics
Institution
Ambient Intelligence | Practical Ethics # Ambient Intelligence - by Stephen Rainey - May 18, 2021 Written by Stephen Rainey An excitingly futuristic world of seamless interaction with computers! A cybernetic environment that delivers what I want, when I want it! Or: A world of built on vampiric data
Read sourceAnalysis · doi.org
Smart Surveillance
Journal · peer-reviewed
# Smart Surveillance Surveillance & Society. Published: 2021-06-25. 9 citations. ## Authors - David Murakami Wood (Queen's University): h-index 23; 2,885 citations - Valerie Steeves (University of Ottawa): h-index 17; 1,203 citations ## Topics - Video Surveillance and Tracking Methods - Smart Cities
Read sourceAnalysis · stevencottingham.com
Ambient surveillance
Other
Ambient surveillance — Steven Cottingham ## Ambient surveillance: Computer vision and animal camouflage The evolution of computer vision has been rapid and intense. As early as the ’60s, the computer eye was able to extract three-dimensional information from images, then learning optical flow, motio
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