A three-member bench headed by Chief Justice of India (CJI) Surya Kant tagged the plea with other pending petitions concerning the recent student protests organised by the Cockroach Janta Party. Appearing on behalf of the petitioner, senior advocate Dr Menaka Guruswamy contended that the plea was filed in the context of the Delhi Police using digital tools to surveil protesters at Jantar Mantar. She added the services of two private entities, Aditya Infotech Ltd and Dimension NXG Pvt Ltd, were being used, and that the data was processed and stored in violation of the Digital Personal Data Protection Act, 2023. She further submitted that the data had been collected without permission. "These private entities host the data in violation of the DPDP Act," she argued. The bench agreed to consider the plea. Rahim has approached the top court seeking a declaration that the use of indiscriminate biometric surveillance at peaceful public assemblies is unconstitutional and should be restrained until Parliament enacts a law specifically authorising and regulating such measures. The plea alleged that Delhi Police conducted biometric surveillance in a "complete legal vacuum". It said neither the Delhi Police Standing Orders governing protests nor the Criminal Procedure (Identification) Act, 2022, authorises biometric surveillance of persons participating in civilian assemblies. According to the plea, Delhi Police carried out automated extraction and matching of protesters' biometric identifiers and allegedly linked the data with permanent national criminal databases.
Aug 13, 2026 · via economictimes.indiatimes.com
The results reaffirm the company's leadership in one of the industry's most demanding and operationally relevant biometric evaluations. COURBEVOIE, France, Aug. 13, 2026 /PRNewswire/ -- IDEMIA Public Security, the leading provider of secure and trusted biometric-based solutions, today announced that its facial recognition algorithm has achieved top performance in the latest National Institute of Standards and Technology (NIST)'s Face Recognition Technology Evaluation (FRTE) 1:N Identification benchmark, reaffirming the company's leadership in one of the industry's most demanding and operationally relevant biometric evaluations. The latest NIST FRTE 1:N Identification results place IDEMIA Public Security #1 in most of the tested scenarios, including the benchmark's two most operationally significant identification scenarios: - #1 in all Mugshot Identification types, including the largest evaluation conducted by NIST against a gallery of 12 million identities, demonstrating robustness and exceptional accuracy at a national scale. - #1 in Visa Border Identification, delivering a significant improvement in performance with identification errors reduced by more than 40% compared with IDEMIA Public Security's previous 2025 submission. - Top Tier in Fairness for False Positive Identification Rate, ensuring that users not only use the most accurate and efficient technology to date but can also be confident that they comply with the most demanding AI regulations in the world. The FRTE 1:N Identification benchmark evaluates how accurately facial recognition systems identify an individual by searching one face against millions of enrolled identities. Considered one of the world's leading benchmarks for facial recognition technology, it evaluates performance in real-world scenarios including mugshot identification, visa processing, border management, law enforcement investigations, and national identity programs. As governments and agencies process millions of travelers and identity transactions every day, achieving both exceptional accuracy and scalability have become essential. These latest NIST results demonstrate IDEMIA Public Security's ability to deliver highly accurate identification across some
Aug 13, 2026 · via prnewswire.com
Brazilians weigh the benefits of AI facial recognition against the costs Loading... | Rio de Janeiro In a downtown office building near Rio de Janeiro’s famous Sambadrome avenue, a dozen police officers sit behind desks staring up at a large bank of computer monitors. Mug shots, camera footage, and interactive maps blink from the screens. This is Rio’s Integrated Command and Control Center, or CICC, the state security forces’ technological nerve center. Facial recognition cameras operated by the military police are a key part of this infrastructure. Using artificial intelligence, smart cameras scan the biometric data of passersby against a database of outstanding arrest warrants. Officers at the CICC are alerted if there’s a match and send the closest patrol to conduct a stop. Why We Wrote This Who suffers when AI gets things wrong? In Brazil, where fighting crime is a top priority for citizens, facial-recognition technology is exploding, even though the legislature is still working on laying out clear rules. Fear of crime that for many outweighs concern for data privacy has made Brazil fertile ground for the mass adoption of these kinds of surveillance technologies. There are more than 560 projects using facial recognition technology across the country – more than double the number in use two years ago, according to civil society organization O Panóptico. The majority are run for public security purposes by local governments or police forces, but they’re also implemented in some private spaces, such as schools. While advocates say smart cameras can help bring down crime, the explosion of this technology without a clear legal framework raises questions about oversight, privacy, and who suffers the most when AI gets things wrong. It’s a public policy that has widespread support, says Thallita Lima, research coordinator at O Panóptico. “Public security is a problem,
Aug 13, 2026 · via csmonitor.com
Vadzo Imaging Introduces Bolt-2020BRS: 20MP AR2020 Raw Bayer MIPI Camera for AI Inspection, OCR, and Embedded Vision Vadzo's Bolt-2020BRS is a 20MP AR2020 Raw Bayer MIPI Camera built on the onsemi HyperLux LP AR2020 sensor, streaming unprocessed 8-bit Bayer data over 4-lane MIPI CSI-2 with sub-10ms latency for AI inspection, OCR, and embedded vision platforms needing direct sensor access for custom ISP pipelines on SoC accelerators, FPGAs, and edge AI platforms. As a board-level AR2020 Bayer MIPI Camera with 100dB HDR and NIR response at 850nm and 940nm, it gives OEM teams full control over image processing rather than a fixed onboard pipeline FORT WORTH, Texas, August 13, 2026 (Newswire.com) - Vadzo Imaging, a provider of embedded vision camera products, today announces the launch of the Bolt-2020BRS, a 20MP AR2020 MIPI Camera built for OEM teams who need direct access to unprocessed high-resolution sensor data rather than a fixed onboard image pipeline. As a 20MP Bayer MIPI Camera delivering 5120x3840 raw output at 1.4 µm pixel pitch over 4-lane MIPI CSI-2, it connects directly to the host SoC ISP, giving integrators the sensor data foundation for hardware-accelerated custom processing on Jetson, Raspberry Pi, and i.MX8M Plus platforms. Technical Problem Definition Many embedded AI inspection, OCR, and machine vision systems fail not because of insufficient resolution but because of processing decisions made before the frame reaches the inference pipeline. A camera module with a fixed onboard ISP applies demosaicing, noise reduction, and tone mapping tuned for general-purpose viewing rather than the feature set for an inspection or recognition model depending on. For AI Defect Inspection Camera Module deployments identifying sub-millimeter surface defects, or OCR MIPI Camera systems extracting character geometry from low-contrast labels, that early processing can discard detail the downstream algorithm needs, with no way to recover it once committed.
Aug 13, 2026 · via newswire.com
British Transport Police is extending its live facial recognition (LFR) trial to the London Underground, despite ongoing privacy and accuracy concerns, according to The Register. The deployment will initially focus on Victoria Underground station before rotating to other stations. The LFR technology, utilizing the NEC NeoFace M40 algorithm, scans faces against a police watchlist, alerting officers to potential matches for review. This expansion follows a pilot at London Bridge railway station and similar deployments by the Metropolitan Police. Critics, including civil liberties group Big Brother Watch, have labeled the technology "dystopian" and "intrusive," citing instances of innocent individuals, particularly from ethnic minorities, being misidentified. Concerns also extend to the routine use of such pervasive surveillance in a democracy and the storage of facial images. A recent survey indicated public apprehension regarding errors and data handling. British Transport Police maintains that images of non-matches are deleted immediately and emphasizes its commitment to lawful, proportionate, and transparent use of the technology to protect the public and combat crime. Kelley Damore is Chief Content Officer at CyberRisk Alliance, where she leads content strategy across the company’s digital brands, research, communities and live events serving CISOs and security practitioners. At CyberRisk Alliance, she is focused on delivering 365-day engagement, trusted journalism and actionable insights to help security leaders navigate an increasingly complex threat landscape. Kelley Damore is Chief Content Officer at CyberRisk Alliance, where she leads content strategy across the company’s digital brands, research, communities and live events serving CISOs and security practitioners. At CyberRisk Alliance, she is focused on delivering 365-day engagement, trusted journalism and actionable insights to help security leaders navigate an increasingly complex threat landscape. Registering with SC Media is 100% free. Join tens of thousands of cybersecurity leaders today and gain access to the latest analysis shaping the global infosec
Aug 13, 2026 · via insight.scmagazineuk.com
Honor's Robot Phone has launched in China with a 4-DoF gimbal camera and the first ARRI color science pipeline built into a smartphone. Here's what's inside, and what it costs. To be totally honest, we were rather skeptical of the Honor Robot Phone when it was first announced. But, following a rollout path that has taken in everything from MWC 2026, Cannes, and the 28th Shanghai International Film Festival, it launched yesterday in China. And above and beyond what we still can’t help thinking of as a bit of a gimmick in the shape of its 4-DoF integrated gimbal camera, it is the first smartphone to feature ARRI color science in its image processing pipeline. ARRI's first smartphone So, let’s start there. The main camera supports 10-bit ARRI LogC3 recording in a dedicated ARRI Cinema mode, combined with ARRI Wide Gamut 3 and built-in, real-time-previewable ARRI Looks. Honor says footage can go straight into the likes of DaVinci Resolve with ARRI LUTs applied as part of a "complete mobile capture-to-post-production workflow." Harald Brendel, ARRI's Director of Image Science, has said that the two companies have calibrated the phone so that it can use the same LUTs as an ALEXA and thus produce “very similar” images. There is a lot more to an imaging pipeline than just that though, and as yet we don’t know the details of bitrate or measured dynamic range (Honor claims 14 stops). Perhaps more importantly, Honor has confirmed the ARRI technology will extend into the upcoming Honor Magic9 Series, which is a far more straightforward, conventional smartphone and is liable to be the one that really introduces ARRI color science into the mass smartphone space. Camera and gimbal details The Honor Robot Phone has three cameras: a dual 200 MP system featuring a 200 MP, 1/1.28-inch,
Aug 13, 2026 · via redsharknews.com
Youverse highlights population-scale facial recognition accuracy in NIST evaluation Youverse says its first submission to the NIST’s ongoing Face Recognition Technology Evaluation 1:N Identification track validates the accuracy of its software as suitable for population-scale fraud detection. The company’s youverse_001 facial recognition algorithm recorded a false-negative identification rate of 0.43 percent at a threshold limiting the False Positive Identification Rate (FPIR) to approximately 0.3 percent when matching frontal mugshot probes against a gallery of 1.6 million mugshots. Youverse expresses this as a 99.57 percent true identification rate. “Independent evaluation by NIST is a major milestone for Youverse and a powerful validation of what we have built,” says Miguel Lourenço, the company’s CPO. “Achieving a 99.57 percent true positive identification rate against a gallery of 1.6 million faces demonstrates that our technology delivers the scale and accuracy demanded by the world’s most critical identity systems,” Lourenço adds. One-to-many identification compares one probe image against an entire gallery to find a possible matching identity. Organizations often use 1:N identification to search large databases for duplicate enrollments or people registered under different identities. When searching a NIST mugshot gallery with 12 million identities, the algorithm recorded a 98.97 percent identification rate. Youverse says this large-scale search capability could support identity deduplication, fraudulent enrollment detection, access control, KYC, and anti-money laundering (AML) processes. The company’s best result by ranking among the main FRTE metrics was matching probe images captured by biometric kiosks against a gallery of 1.6 million visa images. Youverse delivers the facial matching algorithm with liveness detection and says its platform permits one-to-many searches only with explicit user consent. The latest NIST FRTE 1:N results showed that performance continues to converge in controlled comparisons such as frontal mugshot identification. Important performance differences remain when algorithms face more difficult images, including webcam captures,
Aug 13, 2026 · via biometricupdate.com
DHS surveillance spending tops $2.9B as domestic enforcement architecture expands The Department of Homeland Security (DHS) has recorded more than $2.9 billion in contract obligations since January 2021 for technologies capable of watching, identifying, locating and compiling detailed profiles of people inside the United States, according to a new Brennan Center for Justice analysis. An analysis of the Brennan Center’s underlying contract spreadsheet by Biometric Update shows the spending is accelerating. Approximately $1.36 billion in obligations have been recorded since President Donald Trump returned to office, including about $805 million through July 26, 2026—already more than the total identified for any full year from 2021 through 2025. The spending spans facial recognition and other biometrics, drones, commercial data purchases, cellphone extraction and location tools, and AI-driven analytical platforms that combine information from government and private databases. Rather than documenting a single surveillance technology, the report maps an increasingly integrated enforcement architecture in which multiple systems work together to identify, locate and profile people. Biometrics account for the largest share Biometric programs account for approximately $1.1 billion of the obligations identified by the Center, more than any of its other five categories. Much of that amount supports the expansion and maintenance of DHS’s central biometric infrastructure, including its legacy Automated Biometric Identification System (IDENT) and the Homeland Advanced Recognition Technology program intended to succeed it. General Dynamics, Peraton and Science Applications International Corporation are among the principal contractors. Another large portion went to Amentum and Pluribus Digital for collecting biometric and biographical information from applicants seeking immigration related benefits. The category also includes mobile identification systems that bring biometric searches out of controlled enrollment centers and into field operations. Among them is Mobile Fortify, the NEC-developed facial recognition application used by Customs and Border Protection (CBP) and Immigration and Customs Enforcement
Aug 13, 2026 · via biometricupdate.com
Back to Journals » Journal of Multidisciplinary Healthcare » Volume 19 NeuroMimicNet: A Multimodal Neuromorphic Framework for Early Screening and Cognitive Pattern Recognition in Children with Autism Received 24 February 2026 Accepted for publication 7 May 2026 Published 14 August 2026 Volume 2026:19 605039 DOI https://doi.org/10.2147/JMDH.S605039 Checked for plagiarism Yes Review by Single anonymous peer review Peer reviewer comments 2 Editor who approved publication: Dr David C. Mohr Poornima S, Elakya R School of Computer Science and Engineering, Vellore Institute of Technology, Chennai Campus, Chennai, Tamil Nadu, 600127, India Correspondence: Elakya R, Email [email protected] Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition which is composed of social, behavioral, and communication challenges that generally require early detection. Purpose: This research proposes NeuroMimicNet, a brain-like event-driven neuromorphic computing framework designed for early screening and cognitive pattern recognition in children with autism. The framework integrates audio signal and facial expression images as multimodal inputs to capture both neural and behavioral patterns. Methods: The audio modality involves pre-processing steps including noise elimination and normalization, while the neuromorphic processing of audio features is done with Spike-Timing-Dependent Plasticity (STDP), Hebbian learning and a Loihi-inspired spiking neural processing model to capture temporal auditory patterns efficiently. The facial expression images are pre-processed through face alignment, resizing and normalization, and high-level visual features are extracted using a pretrained ResNet50 convolutional neural network. The extracted audio and image features are fused at the feature level to form a unified multimodal representation. The fused features are then classified into four ASD severity level such as Typical, Mild, Moderate, and Severe using a supervised classification model. Results: Performance is evaluated using accuracy, F1-score, precision, recall, and computational efficiency across benchmark EEG-autism datasets. Experimental results demonstrate that NeuroMimicNet achieves higher accuracy and faster response compared to conventional deep learning models.
Aug 13, 2026 · via dovepress.com
| Study shows that quantitative CT analysis of orbital structures offers a potential, objective method for assessing TED activity, enabling clinicians to identify high-risk patients who may require prompt therapeutic intervention. Photo: Bobby Saenz, OD. Click image to enlarge. | In a recent study, researchers aimed to identify a relationship between orbital CT parameters (volume and density) and inflammatory activity in patients with thyroid eye disease (TED). The team found five predictors of active TED, including larger extraocular muscle (EOM) volume and higher intraorbital fat density, suggesting that quantitative CT analysis may be useful for assessing TED activity. The findings were reported in PLoS One. This retrospective study analyzed CT images and clinical records of 85 TED patients and 15 controls. Orbital segmentation was performed using commercially available software. The volumes and densities of the EOMs, intraorbital fat and lacrimal gland were measured. CT parameters were compared among the control, active TED and inactive TED groups. Patients were further classified into two subgroups based on disease severity: mild TED and moderate-to-severe TED. Patients with active TED (defined by a clinical activity score ≥3) demonstrated significantly larger EOM volumes and higher intraorbital fat densities compared to those with inactive TED. Five robust, independent predictors of active TED were found: - shorter disease duration - higher serum thyroid-stimulating immunoglobulin levels - larger EOM volume - higher EOM density - higher intraorbital fat density Combining clinical, serological and quantitative CT metrics resulted in exceptional diagnostic performance, indicated by an area under the ROC curve (AUC) of 0.938. Stratified analysis confirmed that EOM volume and intraorbital fat density remained significantly different between active and inactive TED groups across both mild and moderate-to-severe disease categories. In the moderate-to-severe subgroup, all four extraocular rectus muscles were larger in active TED patients. In the mild subgroup, only
Aug 13, 2026 · via reviewofoptometry.com
The company behind 300,000 Eftpos terminals across Australia is hoping shoppers will want to make payments by simply glancing at a screen, as biometric technology pushes further into retailing. Verifone is selling the innovation as “pay for your coffee with a smile”, promising faster checkouts for people who opt in to having their face or palm-vein – the veins in people’s hands – biometrics used for Eftpos transactions in Australia. It may take a long time before the technology is widely available, however, with cafes, restaurants and retailers required to upgrade their existing equipment. The head of product for Asia Pacific at Verifone, Ben Hughes, said the biometric payments will ease the “friction” of slow transactions. “If you go to a grocery store and you have to tap a loyalty card, plus tap a payment card, that’s the kind of thing that now we’d be able to speed up,” he said. He said the company was expecting retailers to deploy the Verifone Victa devices, which launched last month, incrementally as their current terminals reached their end of life. Hughes said the technology will need buy-in from banks and other organisations that want to allow their customers to pay using biometrics. Biometrics are converted into tokens on the device, he said, meaning images are not stored by Verifone, but biometric profiles are managed by merchants, banks or digital wallet providers. Customers will be able to continue to use contactless payments on their card or phone. Hughes said the company had measures in place to avoid users “spoofing” other people’s hands or faces, as has been seen in the rollout of facial verification technology, similar to that used in age assurance technology for Australia’s social media ban. The company is expecting some pushback on the shift to biometrics, but compared it to
Aug 13, 2026 · via theguardian.com
Dublin, Aug. 12, 2026 (GLOBE NEWSWIRE) -- The "Artificial Intelligence AI" has been added to ResearchAndMarkets.com's offering. Artificial Intelligence Patent Landscape Report 2010-2024: Global Market, Technology and Competitive Analysis The Artificial Intelligence Patent Landscape Report delivers a comprehensive analysis of 244,202 AI patents filed across major jurisdictions between 2010 and 2024. Drawing on international patent filings, the report examines innovation across healthcare, finance, entertainment, agriculture, energy, logistics, industrial automation, retail, manufacturing, transportation, consumer electronics and enterprise software. The analysis combines quantitative patent data, descriptive statistics, artificial intelligence, natural language processing, topic modeling, patent clustering and International Patent Classification-based technology segmentation. It provides actionable intelligence on patent activity, competitive positioning, geographic coverage and emerging innovation opportunities in machine learning, neural networks, natural language processing, computer vision, image and video recognition, pattern recognition, robotics, predictive analytics and intelligent automation. Organized into Landscape Overview, Market and Competitor Analysis, Technology Analysis and Key Players' Patent Profiles, the report supports strategic decision-making in research and development, product innovation, investment, licensing, partnerships, mergers and acquisitions and market entry. Artificial Intelligence Patent Landscape Overview The landscape overview tracks global AI patent trends from 2010 through 2024. The dataset includes 106,684 active patents, 94,075 pending patents and 42,952 inactive, discontinued or expired patents. Filing activity reached its highest level in 2023, when more than 45,000 new patents were recorded. Approximately 95% of the identified patents have been registered since 2019, underscoring the rapid acceleration of artificial intelligence research and commercialization. China leads the global artificial intelligence patent landscape with 115,768 registrations, followed by the United States with 58,671 patents. South Korea, Europe and other jurisdictions account for smaller shares. These results highlight China's dominant filing position and the United States' substantial contribution to global AI innovation. Artificial Intelligence Market and Competitor Analysis The market analysis evaluates global AI
Aug 13, 2026 · via globenewswire.com
Facial detection technologies have gone from commonplace to near-ubiquitous in major cities, prompting some privacy researchers to look for ways to thwart them. Hacker and former CISO Bill Swearingen's noRecognition project can now generate patterns that hide a wearer from cameras, making them useful for t-shirts, face coverings, hats, and other garments to help maintain your privacy. People have been using makeup and specific clothing patterns to trick smart cameras for years, but with improvements in AI and image recognition, this has grown increasingly difficult. The noRecognition project wants to both enhance these apparel countermeasures and make them more readily available, hence the crowdfunding campaign. "Privacy is a fundamental right," Swearingen told TechCrunch, saying he wanted people to be able to opt out of being tracked with something as simple as a choice of clothing. My grandparent's sofa probably would have been invisible to modern facial recognition systems.Credit: noRecognition These patterns will be sold in two different tiers: Standard and One of One. The former will include the mainstream patterns the project generates, giving you broad-spectrum coverage against detection by security and surveillance systems. However, it's possible that AI developers will one day buy these prints and train their models to track them, making them less useful as protective measures. One of One, however, will only be sold in extremely limited numbers: 50 of each pattern across the various clothing options. Once those 50 are sold, that pattern will never be sold again, in theory, making it almost impossible for an AI model developer to use it for training, as its supply and use would be too limited. Swearingen is also releasing his team's numbers to keep the campaign honest. You can see which vision systems the patterns were tested against, how well they work when worn by different people
Aug 12, 2026 · via tech.yahoo.com
On June 22, Western Australian police became the nation’s first law enforcement agency to use live facial recognition technology to find persons of interest. The trial involves a clearly marked van with cameras driving around Perth and Mandurah. It scans the faces of everyone it passes, comparing them against a watchlist of about 4,000 people. It includes those with outstanding arrest warrants, reportable offenders, people subject to lawful exclusion orders, and missing persons. The exercise is overt and widely publicised, with the dates of deployments posted in advance. In its first week, media reports put the trial at more than 130,000 faces scanned and 33 alerts. It led to 18 arrests, along with engagements with registered sex offenders. Work that would have taken weeks of conventional investigative effort has been done in days by a single van. But harder questions surround its governance. Can we really call it a “trial”? Who gets to authorise such deployments? And who checks the safeguards? Can we actually call it a ‘trial’? Any trial of new technology requires success criteria defined in advance, independent evaluation, and the possibility the technology won’t be deployed on a permanent basis after the trial completes. That’s not what seems to be happening in WA. WA police both runs the deployment and compiles the results it publishes, and no independent evaluator has been named. Its own privacy impact assessment says funding is not yet determined, and lists event security among the intended uses. Arrests are an incomplete measure of success, because everyone arrested was already wanted. These are not crimes solved, but simply a known watchlist being worked through more quickly. And an arrest count only records the hits, not the misses. What remains undisclosed is the human cost – any innocent people the system might misidentify and send
Aug 12, 2026 · via theconversation.com
A camera and its software labeled Bill Swearingen as a person. Then it suddenly wasn’t sure — all because of some weird pattern that he held up to disguise himself. I watched it happen from my seat at annual hacker convention Defcon. Swearingen, a longtime cybersecurity professional and founder of the Kansas City security community SecKC, stood onstage in front of a live camera feed as a person-detection system analyzed him. On the giant screen behind him, the software’s confidence score cleared 0.75, the threshold it needed to declare that, yes, there was a human being in the frame. Then Swearingen raised a flat panel covered in a bizarre black-and-white pattern. The score started falling. It slipped below the threshold, eventually landing at 0.21. “No person detected,” the screen announced in bright green letters. It felt like a low-budget magic trick. Swearingen was still standing there, plainly visible to everyone in the room. The software was still receiving the camera image, but it no longer detected a person above the configured confidence threshold. Swearingen has spent the past year searching for patterns that can confuse the computer-vision systems used to identify people. His project is called noRecognition, and its end goal is to create clothing that makes the wearer harder for AI surveillance systems to detect. It’s a fascinating project, but it’s still a work in progress. The camera wasn’t trying to identify him We tend to call this kind of technology “facial recognition,” but surveillance systems can involve several separate layers of AI-based detection. A person detector asks whether a human body is in the frame. A face detector finds and isolates a face. Facial recognition then compares that face with a database and asks whether it knows who the person is. The demonstration I saw targeted the first
Aug 12, 2026 · via cnet.com
ERWIN, N.C. (WTVD) -- The debate over Flock surveillance cameras is intensifying in Harnett County, as citizens and law enforcement clash over the balance between public safety and personal privacy. When the topic came up on a local Facebook group, Erwin resident Mary Henkes says the response was immediate and loud. "When it was brought up on our Facebook group, it just blew up. What, no, we don't want those here. Get them out of here," Henkes recalled. For drivers passing through Erwin, the cameras are easy to miss. Yet, 11 Flock cameras now monitor busy intersections and the town's main entrances, quietly scanning every passing car. The Flock system captures still images of vehicles, recording color, make, and model, and can alert police if a car is reported stolen, a tag matches a wanted person, or a missing individual is in the area. Not everyone is on board. "I don't like it," Henkes said, noting her discomfort with the cameras watching daily comings and goings. She's lived in Erwin for 21 years and questions the need for such technology in rural areas. "I can see having them maybe in a few places, maybe strategic places, but way out here in the country, on country back roads and things, I don't really see a need for it," she said. Another resident, Nashia Ray, echoed those concerns: "I have one, like, right directly close to my kids' daycare. Take them down or just don't make any more," she said. With just 11 officers on staff, Erwin Police Chief Jonathan Johnson says the cameras are a necessary tool in a small department's arsenal. "I know the concerns, you know, and we've got some pretty strict policies in place," Johnson said. Johnson says the department audits camera usage weekly, and Flock's own system
Aug 12, 2026 · via abc11.com
In brief - Bill Swearingen’s noRecognition project generates patterns that stop camera software from classifying what it covers—people, faces, or cars. - The patterns defeated all 11 open-source detection algorithms he tested, including the software behind Flock license plate readers, Axon body cameras, and Clearview AI. - The first public test came Friday at Def Con in Las Vegas: a 2009 Toyota Yaris wrapped in the pattern, driven past a Flock camera. Bill Swearingen spent the past year running one experiment over and over from his home in Kansas City, where he co-founded the SecKC security meetup. About 31 million tests later, he says he can produce patterns on demand that hide whatever they cover from the detection software wired into Flock cameras—the controversial surveillance system being rolled out across America. He showed it in public for the first time Friday at Def Con, working with the YouTube channel Donut Media to cover a 2009 Toyota Yaris in one of his newest patterns and roll it past a Flock camera. “We proved it was effective,” Swearingen told TechCrunch, though he said the wheels were a challenge. Donut Media said video of the demo lands in the next few weeks. The pattern doesn’t blind the camera. Footage still records normally, and a human watching the screen sees a car. What breaks is the layer on top—the object-detection model that decides “that’s a vehicle, that’s a plate, log it.” So basically, feed an AI detector with enough visual noise engineered against its own math and it logs nothing. The car goes back to being a needle in a haystack. That’s adversarial machine learning, and it works because computer vision doesn’t see what you see. A wrap that reads as loud graphic design to a person can read as nothing at all to
Aug 12, 2026 · via decrypt.co
NORTH PORT — The North Port Police Department is seeking a contract with a facial recognition software firm to help in investigations. The software uses artificial intelligence. On Tuesday, a notice of intent to acquire facial recognition software from Clearview AI was announced by the city of North Port in an email. The cost of the service, according to the announcement, is $11,400 for the first year. The second year’s rate is $28,500. Clearview AI, according to its website, is an “American technology company that provides a powerful facial recognition search engine primarily to law enforcement and government agencies.” More than 3,100 law enforcement agencies across the globe use the service, according to the Clearview website. “Clearview AI works by matching an uploaded photo of a face against a massive database of tens of billions of publicly available images scraped from social media, news sites, and the internet,” Clearview AI’s website states. “It converts facial features into unique mathematical vectors to find similar matches within seconds.” Some residents saw the news about the intention of NPPD to acquire the new service and voiced concerns on social media. Concerns over surveillance has become prevalent with the subject of Flock cameras, for example, growing in popularity. The city of North Port does not have Flock cameras; however, it does have other types of cameras across the municipality. NPPD Deputy Chief Chris Morales said facial recognition software is not uncommon, and Clearview is an investigative tool used by law enforcement when a surveillance photo of a person cannot be made out. Clearview, he said, can be used to find characteristics of a person being investigated. Morales said NPPD is not “actively” using the software, but is using it “reactively.” The same practice, according to Morales, is used for surveillance cameras in the city.
Aug 12, 2026 · via yoursun.com
Police are set to deploy live facial recognition technology in Southend later this week as part of continued efforts to tackle crime and keep people safe.
Essex Police confirmed the vans will be in operation on Friday, August 14, and Saturday, August 15, alongside officers visible across the city.
The technology will be used to identify people suspected of serious offences, including drug, violent and sexual crime, as well as theft and breaches of court orders.
Officers say the system has already led to more than 170 arrests in connection with investigations.
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A spokesman for Essex Police said: "As part of our work to keep you safe and tackle crime in Southend we’ll be visible in the city this weekend.
"We have an obligation to make the public aware of a deployment before it takes place which is why we're letting you know."
Images of those not on police watchlists are deleted almost instantly.
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Aug 12, 2026 · via echo-news.co.uk
San Francisco Bars Reverse Course on Face Scanning Machines at Bars After Community Concerns Around 2,000 people had signed a petition calling out the face-scanning technology. A couple of bars in San Francisco’s legendary Castro neighborhood, which had been using facial-scanning machines, have announced they’ll stop doing so after backlash from the local LGBTQ+ community. Back in June, at least three bars in the historically LGBTQ+ district were using something called a Patronscan Guard+, which is a device by a Canadian company that collects biometric and personal data. The devices collect names, addresses, genders, and patron behavior. That data is then stored in a database and shared within a network of subscribers. “We have heard the concerns regarding the use of PatronScan at Badlands and Toad Hall in San Francisco, and we are listening,” Toad Hall announced on Instagram. “Effective immediately, we are pausing the use of PatronScan while we review our ID verification and security practices.” The devices had caused some bar patrons to be concerned about their privacy. “I was just kind of taken aback,” Har Owen told local outlet Gazetteer SF after going to one of the bars on Memorial Day weekend. “Why is this at a gay bar, of all places?” She explained that at this political moment, “it’s really not great to have lists of gay people.” A petition on Fight for the Future against the technology in the Castro bars had gathered around 2,000 signatures, according to SF Gate. “LGBTQ+ venues that use biometric surveillance technology, including facial recognition, must remove it, scrap the data, and apologize to their patrons. All others should commit to keeping their community safe by rejecting surveillance technology—now and forever,” the petition states. A spokesperson from Patronscan told SF Gate that they do not use facial recognition technology but
Aug 12, 2026 · via gomag.com