Two major protests have been scheduled to take place on Saturday in central London, prompting a huge police operation and government action as thousands of officers have been deployed across the capital. Prime Minister Sir Keir Starmer warned in a statement on Friday that Britain was “in a fight for the soul of this country” as authorities confirmed eleven foreign far-right agitators, including US activist Valentina Gomez, have been blocked from entering the UK ahead of the demonstrations. The government said the action was taken to protect communities from “vile hate” and prevent disorder linked to the planned rallies. The Unite the Kingdom march has been organised by far-right activist Tommy Robinson, whose real name is Stephen Yaxley-Lennon, and has been described as a demonstration for “national unity, free speech and Christian values”. The march has coincided with the annual pro-Palestinian Nakba Day march. The Metropolitan Police said up to 4,000 officers were being deployed across London as the protests coincided with the FA Cup Final at Wembley Stadium. The Met have said that officers are expected to use live facial recognition technology, helicopters, drones, dog units, mounted police and armoured vehicles while enforcing strict Public Order Act conditions. The Prime Minister, speaking after visiting the Metropolitan Police command centre, said anyone intending to “whip up hatred and threaten communities” would “face the full force of the law”. He added that while most attendees were expected to be peaceful, the government would act decisively against those spreading extremism. Police have also confirmed new conditions on protest speakers, making organisers responsible for ensuring invited speakers did not use events as a platform for unlawful extremism or hate speech. This has come as thousands more people are expected to attend separate marches in Belfast on Saturday, including a March for Jesus organised
May 16, 2026 · via premierchristian.news
U.S. Army Soldiers assigned to 7th Battalion, 101st Aviation Regiment, 101st Combat Aviation Brigade, 101st Airborne Division (Air Assault), participate in an uncasing and change of responsibility ceremony at Fort Campbell, Kentucky, May 14, 2026. During the ceremony, Lt. Col. Quinn Meyers assumed command of the battalion and Command Sgt. Maj. Frederick Benuzzi assumed responsibility as the battalion uncased its colors in recognition of the unit’s reactivation. (U.S. Army photo by Sgt. Brianna Badder)
| Date Taken: | 05.14.2026 |
| Date Posted: | 05.15.2026 16:39 |
| Photo ID: | 9687213 |
| VIRIN: | 260514-A-JO777-1330 |
| Resolution: | 7650x5464 |
| Size: | 6.27 MB |
| Location: | KENTUCKY, US |
| Web Views: | 3 |
| Downloads: | 1 |
This work, 7-101 Uncasing Ceremony [Image 8 of 8], by SGT Brianna Badder, identified by DVIDS, must comply with the restrictions shown on https://www.dvidshub.net/about/copyright.
May 16, 2026 · via dvidshub.net
Five stories you might have missed in Peterborough - Published The UK's Eurovision entrant, who grew up in Yaxley, near Peterborough, prepared for the competition in Vienna this weekend, while police rolled out facial recognition cameras in the city for the first time. Here are five stories you might have missed from Peterborough this week. Eurovision star's Peterborough beginnings remembered The UK's Eurovision Song Contest entrant, Look Mum No Computer, will grace the stage in Vienna this weekend, but his career had more humble beginnings at a small gig venue in Peterborough. Sam Battle, who grew up in nearby Yaxley, performed across Cambridgeshire as a solo act and as part of bands Yellow Snow and Zibra in his early days, putting him on the radar of BBC Introducing, external. Among the venues he played was The Met Lounge in Peterborough. Steve Jason, its owner, said venues like his were "so important" for upcoming artists as "they have a place to test their material". Rural bus campaigners pleased with new timetable Campaigners who called for changes to a rural bus service to help students and workers have welcomed a new timetable. From June, route 27 between Stamford and Peterborough will run from 07:00 BST Monday to Saturday, 30 minutes earlier than before, and more frequently. The service passes through villages including Wittering, Wansford and Castor and is funded by the Cambridgeshire and Peterborough Combined Authority. Police facial recognition technology rolled out A police force is preparing to use live facial recognition (LFR) technology for the first time to identify individuals wanted by the courts and police, as well as those who pose the greatest risk to public safety. Cambridgeshire Police said the cameras would be deployed in Peterborough city centre on 16 May. The system works by scanning faces from a
May 16, 2026 · via bbc.co.uk
Smart locks are getting smarter, incorporating more advanced technologies that offer you more secure ways to unlock your door. The latest company to offer this is SwitchBot, with its new $170 Lock Vision and $230 Lock Vision Pro. The new smart lock incorporates 3D structured-light facial recognition technology, which the company says enables faster, more effortless unlocking. The Vision Series locks use 20,000 infrared points to create 3D facial maps that SwitchBot says can achieve millimeter-level recognition. The system can unlock a door in a second while resisting spoofing that uses photos or videos. SwitchBot says that the system also works when people are wearing glasses, hats, wigs or makeup. SwitchBot also says this is the world's first smart lock to incorporate face recognition unlocking, though we've seen a similar technology on the Lockly Visage Zeno. "Smart locks with face ID have become fairly common by now, actually," said Tyler Lacoma, CNET's home security and smart home editor, noting that while the face recognition isn't new, the specific 3D structured-light technology behind it may be. A representative from SwitchBot did not immediately respond to a request for comment. The Lock Vision Pro also comes with multiple unlock methods beyond 3D face recognition. It comes with palm vein recognition (an increasingly common feature on newer smart locks) and semiconductor fingerprint unlocking. Palm vein scanning lets you unlock doors without touching the device. There's also app control, NFC, passwords, voice assistants, smartwatch control, autounlocking with geofencing and physical keys as additional options. The lock itself has a 10,000-mAh rechargeable battery that should last 12 months on a single charge with typical usage. It also has a CR123A backup battery that should provide 500 emergency unlocks. If both options are down, people can power the smart lock via an external USB-C port, though
May 16, 2026 · via cnet.com
SwitchBot today debuted the SwitchBot Lock Vision and the Lock Vision Pro, two Matter-enabled smart locks that include facial recognition technology for quick door unlocking. With Matter-over-WiFi, the locks are compatible with HomeKit and they support NFC, so you can use them with an Apple Home setup. SwitchBot also included "advanced 3D structured light" facial recognition that's able to recognize approved lock users in under one second. SwitchBot says the facial recognition is comparable to 3D facial recognition used by "flagship smartphones," and it can't be spoofed with photos or videos, even when wearing glasses, hats, or makeup. It uses more than 20,000 infrared dots to create an accurate 3D facial map that SwitchBot says is capable of millimeter-level recognition. The locks also include multiple other unlocking methods, including NFC, passwords, iPhone app controls, the Apple Watch, Siri-based voice commands, geofencing, and physical keys. The Pro version of the lock adds palm vein and fingerprint access too, for even more ways to get into your house. Palm vein detection works without touching the lock, even if hands are wet or dirty. SwitchBot's Lock Vision and Lock Vision Pro have 12-month battery life and emergency backup power options. They are meant to replace a standard deadbolt, and include mmWave radar detection to determine when someone is approaching the door. No hub is required for the locks, and biometric data is stored on-device. The SwitchBot Lock Vision is priced at $170, while the SwitchBot Lock Vision Pro is available for $230. SwitchBot has a $40 launch discount on Amazon and on its website.
May 15, 2026 · via macrumors.com
Photo to Recipe – Food Scanner is an AI-powered mobile application designed to transform food photos into structured home-cooking recipes. By analyzing an image of a dish, the app generates ingredient lists and step-by-step cooking instructions intended to replicate the meal in a home kitchen environment. Instead of requiring users to search for similar recipes manually, the tool interprets visual cues such as ingredients, plating style, and preparation method to infer how a dish may be made. This creates a fast bridge between food discovery and practical cooking guidance. Photo to Recipe – Food Scanner is positioned for home cooks and food enthusiasts who want to turn visual inspiration into actionable cooking steps. By combining image recognition with recipe generation, it reduces the gap between eating and cooking inspiration in everyday use. Food Recognition Apps Photo To Recipe Converts Meal Images Into Instant Cookable Recipes Trend Themes - Visual-to-recipe Conversion — This trend enables automated transformation of meal images into structured recipes, creating possibilities for personalized, context-aware recipe generation integrated into everyday food discovery. - AI-ingredient Inference — By deducing ingredient lists from visual cues, systems can support granular inventory suggestions and tailored substitution logic that adapts to dietary restrictions and pantry constraints. - Instant Home-cooking Guidance — Real-time conversion of visual inspiration into step-by-step instructions introduces the prospect of seamless transitions from dining-out or social media discovery to practical at-home cooking experiences. Industry Implications - Consumer Food Tech — Food-focused apps and platforms can embed image-to-recipe capabilities to deepen user engagement and enable new monetizable features around personalization and ingredient commerce. - Meal Kit and Grocery Retail — Retailers and meal-kit providers could leverage visual recognition to recommend purchasable ingredient bundles that mirror photographed dishes, enhancing conversion from inspiration to purchase. - Culinary Education and Content — Cooking schools,
May 15, 2026 · via trendhunter.com
Dr. David Clausi, a University Research Chair and professor in the Department of Systems Design Engineering, has been awarded the Ontario Professional Engineers Award (OPEA) Engineering Medal in Research and Development. “I’m deeply honoured to receive this recognition from Professional Engineers Ontario,” said Clausi. “This work reflects a commitment to advancing methods that help us better understand our changing planet, made possible by outstanding students, collaborators, and partners. Mentoring emerging researchers and seeing their impact beyond the lab has been especially rewarding.” Clausi is co-director of the Vision and Image Processing Research Group (VIP) and a researcher whose impact spans satellite image analysis, automated skin cancer detection, whale detection, as well as sports statistical and video analytics. His innovations have benefited the Canadian Space Agency, Environment Canada and Fisheries & Oceans Canada, as well as companies across the aerospace, biomedical, remote sensing and sports sectors. A dedicated mentor, Clausi has supervised over 75 graduate students, several of whom have launched successful startups or made significant contributions in the computer vision field. He is a fellow of the Canadian Academy of Engineering, the Engineering Institute of Canada, and the Asia-Pacific Artificial Intelligence Association and was most recently elevated to an Institute of Electrical and Electronics Engineers (IEEE) fellow in early 2026. Clausi will receive the medal at the OPEA gala on November 13, 2026, in Vaughan, Ontario.
May 15, 2026 · via uwaterloo.ca
A hotel check-in system left more than 1 million customer passports, driver’s licenses, and selfie verification photos to the open web after a security lapse. The data is now offline after TechCrunch alerted the company responsible. The hotel check-in system, called Tabiq, is maintained by the Japan-based tech startup Reqrea. According to its website, Tabiq is used in several hotels across Japan and relies on facial recognition and document scanning to check guests in. Independent security researcher Anurag Sen contacted TechCrunch earlier this week after discovering that the system was leaking the sensitive documents of hotel guests from around the world. Sen said this was because the startup set one of its Amazon cloud-hosted storage buckets, which the check-in system uses to store customer data, to be publicly accessible. The data inside could be viewed by anyone using a web browser, without needing a password, by knowing only the bucket name: “tabiq.” Sen alerted TechCrunch in an effort to help notify the company. Reqrea locked down the storage bucket after TechCrunch reached out to both the company and Japan’s cybersecurity coordination team, JPCERT. This latest lapse underscores a recurring problem of companies exposing or spilling their customers’ personal information and sensitive documents — not through sophisticated attacks, but by failing to follow basic cybersecurity practices. Aside from a recent buzz of AI-discovered vulnerabilities and new cybersecurity capabilities, oftentimes sizable security incidents stem from human error, misconfigurations, or failing to adhere to cybersecurity best practices. In an email acknowledging the exposure, Reqrea director Masataka Hashimoto told TechCrunch: “We are conducting a thorough review with the support of external legal counsel and other advisors to determine the full scope of exposure.” Reqrea said it does not know how the storage bucket became public. By default, Amazon’s cloud storage buckets are private. After
May 15, 2026 · via techcrunch.com
SwitchBot unveils world’s first smart door lock with 3D facial recognition SwitchBot is expanding its smart home locks portfolio by launching the new Lock Vision series smart door locks. SwitchBot has introduced two models under the Lock Vision series, the Lock Vision and the Lock Vision Pro. The latest offering from SwitchBot is advertised as the world’s first smart deadbolt lock equipped with 3D structured-light facial recognition technology. SwitchBot is inspired by the same core technology used in flagship smartphones. According to the brand, the Lock Vision series projects over 20,000 infrared points to create highly accurate 3D facial maps capable of millimeter-level recognition. On top of this, SwitchBot claims that the system unlocks doors in under one second. Besides, the Lock Vision series offers multiple unlock methods, including app control, NFC cards, passwords, voice assistant, smartwatch control, auto-unlock via geofencing, physical keys, palm vein recognition, and semiconductor fingerprint unlocking. The security gadget uses infrared sensing technology for palm vein recognition, which is the same technology found on the Anker Eufy FamiLock E34. This enables users to unlock doors without touching the device, even when hands are wet, dirty, or difficult to scan with conventional fingerprint readers. A high-capacity 10,000 mAh rechargeable lithium battery powers the Lock Vision series, with a specified runtime life of around 12 months. Moreover, both gadgets support Matter-over-Wi-Fi, allowing users to connect directly with supported smart home ecosystems. SwitchBot has incorporated a six-tier security protection system covering locking security, unlocking security, communication security, alarm security, and power security. Other features include tamper alerts, IP65 water and dust resistance, remote unlock confirmation, forced unlock protection, emergency SOS fingerprint recognition, and automatic lockout after repeated failed verification attempts. As for price, the SwitchBot Lock Vision Pro is priced at $229.99/CA$299.99 and the Lock Vision costs $169.99/CA$229.99. Both
May 15, 2026 · via notebookcheck.net
Arrest warrant rejected: AI hit is only a vague hint for judges A district court slows down the use of facial recognition and strengthens the rights of defendants against opaque IT investigation tools. In the world of law enforcement, automated successes in manhunts sound efficient: an image, a database match, a hit. However, what is technically possible does not always withstand legal scrutiny. The Reutlingen District Court made it clear in a decision published on February 11: Algorithmically generated identification clues are not sufficient without sound substantiation and technical transparency to put someone behind bars. The proceedings originated from an incident in a drugstore in October 2025. Employees observed via video surveillance how a person stole several bottles of women's perfume. When the suspect entered the store again a short time later and was approached, it escalated: fleeing, the perpetrator swung around with an umbrella and hit two employees who were trying to hold him. The police used the video material for a facial recognition search at the Federal Criminal Police Office (BKA). The system delivered a hit: a man known to the police, who was already wanted for other offenses. Based on this “match” and the blanket classification as having a prior record, the public prosecutor's office applied for an arrest warrant for robbery. “Ominous” Software: Reprimand lacking Transparency The Reutlingen District Court ( 5 Gs 19/26). The reasoning attacks the current practice of AI-supported investigations. The judges described the facial recognition software used as downright “ominous.” The accusation: Neither the functionality nor the algorithm, the reference data used, nor the error rates were comprehensibly documented. The BKA operates the official police facial recognition system (GES). Last year, German authorities used the technology significantly more often for identifying people than before. With a total of around 343,856 searches in
May 15, 2026 · via heise.de
Eleven 'far-right agitators' banned from UK ahead of rally, government says Eleven foreign "far-right agitators" have been blocked from entering the country to attend a rally organised by anti-Islam activist Tommy Robinson, the government has said. Thousands are expected to join the Unite the Kingdom event on Saturday, while an annual pro-Palestinian demonstration takes place in another part of London. Sir Keir Starmer said "we're in a fight for the soul of this country" ahead of the protest. The Metropolitan Police is anticipating one of its busiest days in recent years, and has drafted more than 4,000 officers over fears of clashes if the rival protests coincide. In a statement on Friday, Sir Keir said: "We're in a fight for the soul of this country, and the Unite the Kingdom march this weekend is a stark reminder of exactly what we are up against. "Its organisers are peddling hatred and division, plain and simple. We will block those coming into the UK who seek to incite hatred and violence. "For anyone who sets out to wreak havoc on our streets, to intimidate or threaten anyone, you can expect to face the full force of the law". The BBC has approached Unite the Kingdom for comment. In a post on X on Friday, Robinson - whose real name is Stephen Yaxley-Lennon - wrote: "Keir Starmer's regime are the enemy of the British people. Descend on London." Among the 11 blocked from entering the UK is the US-based, anti-Islam influencer Valentina Gomez, who attended the first Unite the Kingdom march last September. While that rally began largely peacefully, there were a series of violent confrontations with police and anti-Muslim hate speech incidents. Protesters are due to gather at Parliament Square on Saturday, while the separate pro-Palestine Nakba Day march begins at Waterloo
May 15, 2026 · via bbc.com
Abstract Facial recognition is increasingly adopted for automated classroom attendance; however, real-world deployment in schools remains constrained by privacy risks, ethical obligations, demographic bias, spoofing threats, and limited computational resources. Recent incidents involving Microsoft Teams in New South Wales in 2025 and Chelmer Valley High School in the United Kingdom show how poorly governed systems violate student rights and regulatory compliance. Despite growing adoption, many existing attendance systems focus narrowly on recognition accuracy or efficiency, while overlooking spoof resistance, open-set identity handling, fairness mitigation, auditability, and privacy protection. This paper presents LaED, a lightweight, edge-aware, and explainable deep learning framework for privacy-preserving classroom attendance in resource-constrained educational environments. The framework combines multimodal spoof detection, open-set facial recognition, and fairness-aware representation learning within a unified edge-based design. Spoofing attacks, including replay and deepfake attempts, are mitigated through the fusion of physiological and temporal facial cues, while unknown identities are explicitly rejected to reduce proxy attendance. To support responsible deployment, LaED incorporates federated learning with differential privacy, ensuring that biometric data remain local to schools while enabling accountable model updates. Experimental evaluation on CASIA-FASD, CelebA-Spoof, DFDC, FairFace, and a consent-driven classroom dataset shows that LaED achieves over 97.8% recognition accuracy, APCER and BPCER values below 2%, demographic fairness gaps under 2%, and inference latency below 150 milliseconds on edge hardware. Additional tests confirm reliable operation under realistic classroom conditions. These results demonstrate that regulation-aligned and trustworthy facial attendance is feasible on low-cost devices, offering a practical pathway for responsible biometric AI in education. Similar content being viewed by others Introduction Facial recognition technologies have rapidly gained traction for automating administrative tasks across diverse domains, including law enforcement, border control, healthcare, and education1,2,3. In classroom contexts, automated attendance systems are promoted as a means to reduce manual errors, save instructional time, and enable
May 15, 2026 · via nature.com
Inspired by the same core technology used in flagship smartphones, the Lock Vision Series projects over 20,000 infrared points to create highly accurate 3D facial maps capable of millimeter-level recognition. The system unlocks doors in under one second while effectively resisting spoofing attempts using photos or videos. Unlike traditional fingerprint-based solutions, the technology works reliably even when users are wearing glasses, hats, wigs, or makeup. Smarter, Hands-Free Unlocking for Every Household The Lock Vision Series offers multiple unlock methods, including 3D facial recognition, app control, NFC cards, passwords, voice assistants, smartwatch control, auto-unlock via geo-fencing, and physical keys. SwitchBot Lock Vision Pro further expands biometric access with contactless palm vein recognition and semiconductor fingerprint unlocking. Using near-infrared sensing technology, palm vein recognition enables users to unlock doors without touching the device, even when hands are wet, dirty, or difficult to scan with conventional fingerprint readers. By storing all biometric information locally with AES-128 encrypted communication, the Lock Vision Series prioritizes both privacy and security. Built for Long-Term Reliability To reduce concerns around battery anxiety and lockouts, the Lock Vision Series features SwitchBot's DualPower™ and DualBackup™ systems. A built-in 10,000mAh rechargeable battery can power the lock for up to 12 months on a single charge under typical usage conditions, while an additional CR123A backup battery provides up to 500 emergency unlocks. In emergency situations, users can also temporarily power the device via the USB-C emergency power port (the port provides temporary power and does not charge the lock). To further improve power efficiency, the lock utilizes mmWave radar detection, activating biometric recognition only when someone approaches the door. The SwitchBot app also provides real-time battery monitoring and low-battery notifications. Matter-over-WiFi Connectivity Without a Hub The Lock Vision Series supports Matter-over-WiFi, allowing users to connect directly with supported smart home ecosystems without
May 15, 2026 · via manilatimes.net
Today SwitchBot is debuting its all-new SwitchBot Lock Vision and Lock Vision Pro with some notable launch deals at up to $40 off via its official Amazon storefront. As detailed in our launch coverage, the highlights include Matter-over-WiFi with no SwitchBot hub required, the brand’s new 3D facial recognition, and, on the pro model, fingerprint recognition and contactless palm scanning tech that neatly slides into your Apple home setup. There are a pair of new models debuting today with launch discounts: - SwitchBot Lock Vision $130 (Reg. $170) - SwitchBot Lock Vision Pro $190 (Reg. $230) A complete rundown of everything you need to know on both models awaits right here, but we will leave you with some highlights from the new Matter-over-WiFi Lock Vision Series below: - Designed to fit most standard deadbolt locks for easy installation. - Matter-over-WiFi for Matter 1.4, and available to work on Apple Home (certificate in process). - Advanced Unlock Methods: Up to 19 unlock methods, including 3D structured-light facial recognition, contactless palm print recognition (Lock Vision Pro only), and semiconductor fingerprint unlocking (Lock Vision Pro only). - Advanced Power System: DualPower™ and DualBackup™ systems deliver up to 12 months of use on a single charge, with support for up to 500 emergency unlocks and Type-C emergency charging. - Advanced Security Protection: Includes alarm, locking, unlocking, communication, storage, and power security systems, along with IP65-rated water and dust resistance. FTC: We use income earning auto affiliate links. More. Comments
May 15, 2026 · via 9to5toys.com
SwitchBot launches world's first smart deadbolt lock with 3D facial recognition technology There are 9 other unlocking methods too QUICK SUMMARY SwitchBot has launched its new Lock Vision Series, introducing what it claims are the world’s first smart deadbolt locks with built-in 3D facial recognition technology. Available in standard and Pro models, the new locks combine fast facial unlocking with alternative methods including fingerprint scanning, palm vein recognition and app control, whilst also offering up to 12 months of battery life and simple DIY installation. Announced today, SwitchBot has launched its new SwitchBot Lock Vision Series, consisting of the SwitchBot Lock Vision and SwitchBot Lock Vision Pro. The new models are labelled as the world’s first smart deadbolt locks to feature advanced 3D structured-light facial recognition technology. Whilst we’ve seen facial recognition arrive on smart locks before – including last year’s SwitchBot Lock Ultra Vision Combo – SwitchBot says these are the first deadbolt-style smart locks to use the technology in this way. For now, the range is launching exclusively in the US, priced at $299.99 for the Lock Vision Pro and $169.99 for the standard Lock Vision. Both are available through Amazon and SwitchBot’s online store. The facial recognition system is inspired by the same type of technology used in flagship smartphones, projecting over 20,000 infrared points to create highly detailed 3D facial maps with millimetre-level accuracy. It’s also designed to work reliably even if you’re wearing glasses, hats or makeup – something cheaper facial recognition systems often struggle with. If facial recognition isn’t really your thing, both locks support a huge range of alternative unlocking methods too. Alongside app control and physical keys, users can unlock via NFC cards, passwords, voice assistants, smartwatches and auto-unlock geo-fencing features. The locks also support contactless palm vein recognition and semiconductor fingerprint
May 15, 2026 · via t3.com
TOKYO, May 15, 2026 /PRNewswire/ -- SwitchBot, a leading provider of smart home automation and embodied AI products, today announced the launch of the SwitchBot Lock Vision Series in North America, consisting of SwitchBot Lock Vision and SwitchBot Lock Vision Pro. Designed to elevate smart home entry, the Lock Vision Series is the world's first smart deadbolt lock equipped with advanced 3D structured-light faiacial recognition technology, delivering faster, safer, and more effortless unlocking for modern households. Inspired by the same core technology used in flagship smartphones, the Lock Vision Series projects over 20,000 infrared points to create highly accurate 3D facial maps capable of millimeter-level recognition. The system unlocks doors in under one second while effectively resisting spoofing attempts using photos or videos. Unlike traditional fingerprint-based solutions, the technology works reliably even when users are wearing glasses, hats, wigs, or makeup. Smarter, Hands-Free Unlocking for Every Household The Lock Vision Series offers multiple unlock methods, including 3D facial recognition, app control, NFC cards, passwords, voice assistants, smartwatch control, auto-unlock via geo-fencing, and physical keys. SwitchBot Lock Vision Pro further expands biometric access with contactless palm vein recognition and semiconductor fingerprint unlocking. Using near-infrared sensing technology, palm vein recognition enables users to unlock doors without touching the device, even when hands are wet, dirty, or difficult to scan with conventional fingerprint readers. By storing all biometric information locally with AES-128 encrypted communication, the Lock Vision Series prioritizes both privacy and security. Built for Long-Term Reliability To reduce concerns around battery anxiety and lockouts, the Lock Vision Series features SwitchBot's DualPower™ and DualBackup™ systems. A built-in 10,000mAh rechargeable battery can power the lock for up to 12 months on a single charge under typical usage conditions, while an additional CR123A backup battery provides up to 500 emergency unlocks. In emergency situations, users
May 15, 2026 · via prnewswire.com
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May 15, 2026 · via iopscience.iop.org
Facial Recognition Cameras to Debut in Peterborough City Centre Police introduce new technology to identify wanted people and boost public safety State-of-the-art facial recognition cameras will be used in Peterborough city centre for the first time this Saturday. Police are bringing in Live Facial Recognition (LFR) technology to help officers quickly spot individuals wanted for criminal offences or with outstanding arrest warrants. The system works by comparing faces in a live camera feed against a police watchlist, flagging possible matches for officers to review. Police say images flagged as a match are checked and then deleted after use, while other data is removed automatically. “LFR supports policing by identifying wanted people, ensuring they are brought to justice swiftly." Assistant Chief Constable John Massey said. “It is another tool at our disposal in our drive to reduce crime and create a safer county. “While this capability is new to Cambridgeshire, it has been used across policing and security services for some time and has improved greatly, even outperforming its anticipated accuracy and success rate. “We know the community will have a lot of questions about the use of advanced technology within policing and officers will be on hand to engage with the community and answer any queries they may have.” The equipment, borrowed from Bedfordshire Police, aims to make the city safer and tackle crime swiftly. Signs will mark the areas where the cameras are being used, with officers on hand to answer questions from the public.
May 15, 2026 · via planetradio.co.uk
You’re trying to book concert tickets before they sell out. You click the link and before you can make the payment, you’re asked to identify traffic lights, bicycles or blurry crosswalks in a grid of tiny images. Again. For many people, this has become a routine part of life. Logging into financial apps, shopping online or creating accounts increasingly involves “proving you are human”. These systems are known as CAPTCHA. Why are they everywhere? The short answer is that websites are fighting a rapidly escalating war against bots: automated software that imitate human behaviour online. And thanks to advances in artificial intelligence (AI), those bots are becoming even smarter, cheaper and harder to detect than ever before. Why websites need proof you are human Huge amounts of online traffic now come from automated systems. Some are helpful, such as search engine crawlers indexing pages for Google search. Others are far less welcome, and may involve phishing, spam, fake accounts, passwords violation, misinformation, and distributed denial of service attacks overloading web servers. In some areas, AI agents now generate automated online traffic that exceeds human traffic altogether. Modern AI systems can generate convincing text, imitate browsing patterns and even solve some CAPTCHA puzzles. At the same time, companies are increasingly worried about bots scraping online content to train AI systems. As a result, more websites are adding verification systems simply to keep abuse under control. How CAPTCHA actually works CAPTCHA stands for “Completely Automated Public Turing test to tell Computers and Humans Apart”. The original idea was simple: give users a task humans find easy, but computers find difficult. Early CAPTCHA systems often involved distorted text. Later versions switched to image-recognition tasks such as selecting all the squares containing traffic lights or bicycles. Google’s reCAPTCHA became one of the best-known examples.
May 15, 2026 · via theconversation.com
Facial recognition lawsuit raises questions about AI use in policing RENO, Nev. — Artificial intelligence is becoming more common in law enforcement, with agencies across the country using technology designed to help officers identify suspects, analyze information and respond faster. But a federal lawsuit filed in Nevada is raising new questions about what happens when that technology gets it wrong. The case, Killinger v. Jager/City of Reno, centers on an incident at the Peppermill Resort Spa Casino in Reno, where Jason Killinger was detained after facial recognition software allegedly misidentified him as a banned individual. According to court filings, police detained Killinger for identification after receiving the facial recognition alert. Fingerprints later confirmed he was not the person flagged by the system, and he was released. The lawsuit, filed in U.S. District Court in Nevada, alleges false arrest and unlawful detention under the Fourth Amendment. The complaint also claims officers relied too heavily on facial recognition technology without proper verification. RELATED: Baltimore County police release body cam of teen being detained, AI mistakes chips for gun RELATED: Increased use of artificial intelligence in police work could cause problems in cases The case has since been expanded to include the City of Reno as a defendant, raising broader questions about law enforcement policies, officer training, and safeguards surrounding the use of artificial intelligence. Experts interviewed by News 4 said the risks tied to facial recognition technology go beyond simple mistakes. “When these systems are wrong, the consequences are falling on real people,” said Drew Simshaw, a professor at the UNLV William S. Boyd School of Law. Simshaw said concerns include privacy, constitutional protections, and the possibility that some facial recognition systems may perform less accurately across different demographic groups, including people of color. “There could be Fourth Amendment concerns around tracking
May 15, 2026 · via mynews4.com