Artificial Intelligence Camera Market Trends: Smart Surveillance, Deep Learning Integration & Forecast to 2034 How AI-powered imaging, real-time analytics, and intelligent surveillance systems are transforming security monitoring and automation capabilities in the artificial intelligence camera market According to IMARC Group's latest research publication, The global artificial intelligence (AI) camera market size reached USD 9.0 Billion in 2025. Looking forward, IMARC Group expects the market to reach USD 27.2 Billion by 2034, exhibiting a growth rate (CAGR) of 12.74% during 2026-2034. The growing concerns regarding safety and security, rising adoption of AI-powered CCTV cameras, augmenting sales of premium feature-rich smartphones, and increasing product applications in traffic monitoring and homeland security represent some of the key factors driving the market. How AI is Reshaping the Future of the Artificial Intelligence Camera Market - Predictive Threat Detection and Behavioral Analytics: AI-powered camera systems use deep learning models to identify suspicious behavioral patterns in real time, going far beyond passive video recording. Airports, banking halls, and government buildings are deploying these systems to detect anomalies before incidents escalate. Financial institutions using AI-based surveillance have reported measurable reductions in fraud incidents, as facial recognition and motion-pattern analysis work continuously across high-traffic zones without human fatigue. - Face Recognition and Automated Access Control: The shift from badge-based entry to AI camera-driven biometric access is accelerating across corporate campuses, healthcare facilities, and transit hubs. These systems cross-reference live facial data against registered databases in milliseconds, granting or denying access without physical contact. In large urban transit systems handling millions of daily commuters, this technology significantly cuts bottlenecks at entry points while simultaneously flagging individuals on watchlists. - Computer Vision for Industrial Quality Assurance: Manufacturing lines across automotive, electronics, and food processing sectors are integrating AI cameras to automate visual inspections. These systems detect micro-defects, surface irregularities, and
Jun 1, 2026 · via vocal.media
The standard popular framing of human facial recognition treats it as a problem so complex that large brains and specialised neural regions are required to solve it. The human fusiform face area, a section of the temporal lobe that activates specifically when a person looks at a face, has been studied for decades as the neural basis for this ability. The framing is plausible. It is also, by a 2005 finding that has been replicated and extended in the years since, not quite right. Honeybees, with brains roughly one millimetre across containing about a million neurons, can be trained to recognise individual human faces. The result was published in the Journal of Experimental Biology by Adrian Dyer, then at Johannes Gutenberg University in Mainz and the University of Cambridge, working with Christa Neumeyer of Mainz and Lars Chittka of Queen Mary, University of London. According to the team’s 2005 paper, individual bees trained on photographs from a standard human psychology test could discriminate a target face from a similar distractor face with greater than 80 percent accuracy, and could continue to recognise the trained face two days after training. The bees had never previously been exposed to human faces in any evolutionary or developmental sense. They learned the task because Dyer’s team offered them sugar water for getting it right. How the experiment worked The methodology took advantage of the bees’ famously robust associative learning capabilities. Bees are accomplished pattern learners; they have to be, because the flowers they forage from come in an enormous diversity of shapes and colours, and accurate recognition of rewarding flower types is central to their lives. Dyer reasoned that the same machinery might be applicable to any visual pattern, including one with no evolutionary relevance to the bee at all. The team presented bees
Jun 1, 2026 · via spacedaily.com
AI Decodes Centuries-Old Manuscripts and Ciphers Researchers are using machine learning and neural networks to read damaged, encrypted, and hard-to-decipher historical texts, according to reporting by Digital Trends, the BBC, and Nature. The BBC reports a team led by computational linguist Beáta Megyesi used machine learning to help decode a 408-page Vatican manuscript encoded with 34 obscure symbols and some Arabic, revealing medicinal recipes and remedies; Megyesi is quoted saying, "It is like detective work where every symbol, pattern, and partial solution may bring us closer to someone's secrets and to a lost historical world," (BBC). Nature reports neural-network pipelines and projects such as Fragmentarium are helping to recover text from carbonized Roman scroll fragments from Herculaneum and to digitize tens of thousands of cuneiform tablets. Digital Trends describes broader efforts to train models on historical handwriting and linguistic patterns so systems can restore missing or damaged words. Editorial analysis: These developments expand the volume of readable historical data and create new interdisciplinary workflows for digital-humanities practitioners. What happened Researchers are increasingly applying machine learning and neural networks to recover text from damaged, encrypted, or otherwise unreadable historical documents, as reported by Digital Trends, the BBC, and Nature. The BBC reports a team that includes computational linguist Beáta Megyesi used machine learning to help decode a 408-page Vatican manuscript coded with 34 obscure symbols and some Arabic, revealing recipes and remedies; Megyesi said, "It is like detective work where every symbol, pattern, and partial solution may bring us closer to someone's secrets and to a lost historical world," (BBC). Nature reported that neural-network pipelines and digitization efforts such as Fragmentarium are being used to read carbonized papyrus fragments from Herculaneum and to aggregate tens of thousands of cuneiform records for analysis (Nature). Technical details Editorial analysis: Public reporting highlights two
Jun 1, 2026 · via letsdatascience.com
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Jun 1, 2026 · via moomoo.com
Microsoft ends support for Internet Explorer on June 16, 2022. We recommend using one of the browsers listed below. Please contact your browser provider for download and installation instructions. June 1, 2026 NTT, Inc. News Highlights: TOKYO — June 1, 2026 — NTT, Inc. (Headquarters: Chiyoda-ku, Tokyo; President and CEO: Akira Shimada; hereinafter "NTT") has established Rationale-Enhanced Decoding, a new inference framework designed to improve the reliability of outputs generated by multimodal foundation models that process both images and language. The technology addresses a key issue in CoT reasoning by LVLMs: the tendency to ignore self-generated rationales. Unlike conventional inference methods, the proposed approach separately performs image-based inference and rationale-based inference, then combines them through ensemble decoding. This enables the model to generate responses grounded in information derived from both visual inputs and rationales. This research will be presented at the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2026(*1), one of the world's premier international conferences in the field of computer vision, to be held in Denver, Colorado, USA, from June 3 to June 7, 2026. In recent years, the development of Large Vision-Language Models (LVLMs), which integrate Large Language Models (LLMs) with pretrained image encoders, has significantly advanced multimodal reasoning capabilities. Unlike text-only LLMs, LVLMs can directly process visual inputs in addition to text, enabling their use as a foundation for complex multimodal reasoning tasks based on visual content, such as video analysis and document understanding, which are difficult to address using text alone. Similar to LLMs that operate solely on text inputs, Chain-of-Thought (CoT) reasoning has also been regarded as an effective approach for improving inference performance and enabling explainable reasoning in LVLMs. In CoT reasoning, the model first generates intermediate rationales from visual and textual inputs, then appends those rationales to the input sequence to
Jun 1, 2026 · via group.ntt
As South African firms deepen ties with the world’s second-largest economy, local executives flying into Beijing or Shanghai are stepping into a digital system they might never be able to leave. Picture a South African multinational nearing the final stages of a Chinese joint-venture negotiation. Months of closed-door meetings have already shaped pricing, expansion plans and the transfer of proprietary technology. These details are known only to a tightly controlled group of executives on both sides. Then, almost imperceptibly at first, the dynamics shift. A domestic Chinese competitor begins to move with unusual foresight, aligning its products and offers in ways that render the joint venture moot. Nothing is ever publicly leaked and no breach is officially confirmed, yet the coincidence is too difficult to ignore. Inside the company, confidence in the process is hollowed out, replaced by a persistent question that no-one can fully answer: how did this happen? The reality is that across sectors, cases such as this have become common. In fact, disclosures by cybersecurity researchers at NetAskari have exposed a highly automated, internet-based intelligence dashboard used by Chinese state security known as the “dynamic control platform for foreigners”. According to investigative reports, this portal operates as a centralised intelligence system where local police and state agents log in to access extensively documented, searchable visual profiles. Rather than just tracking names the platform aggregates fragmented data points to build an instantaneous, real-time “holographic file” on foreign nationals. In an economy where major industries are still dominated by state-owned enterprises and the boundaries between government oversight and commercial operations are frequently blurred, the existence of such comprehensive data sets creates an inescapable environment of informational asymmetry. The data collection starts at the consulate, pulling information directly from entry visa applications ― including passport numbers, digital ID photos and
Jun 1, 2026 · via businessday.co.za
AI Awareness Training for PM Vishwakarma Beneficiaries Held at DIC Kargil. AI Awareness Training for PM Vishwakarma Beneficiaries Held at DIC Kargil. Kargil, May 30, 2026: The State Project Management Unit (SPMU), PM Vishwakarma, organized an Artificial Intelligence (AI)-based Capacity Building and Awareness Training Programme for PM Vishwakarma beneficiaries in collaboration with the District Industries Centre (DIC), Kargil, at the Conference Hall of DIC Kargil. The programme was conducted in line with the vision of Digital India and IndiaAI to enhance digital awareness and technology adoption among traditional artisans and craftspeople. More than 100 PM Vishwakarma beneficiaries representing various traditional trades and crafts from across Kargil district participated in the training programme. The training session was delivered by Khushbu Joshi, SPMU PM Vishwakarma, and Lobzang Lungtok, IPO, DIC Kargil, who introduced participants to the practical applications of Artificial Intelligence from the perspective of Vishwakarma artisans and craftspeople. The resource persons highlighted various challenges faced by beneficiaries and explained how AI-powered tools can support them in improving productivity, marketing their products, enhancing customer outreach, generating business ideas, and accessing information more efficiently. A hands-on demonstration was also conducted on popular AI applications, including ChatGPT and Gemini, enabling participants to gain practical experience in using these tools for their professional and business needs. During the session, participants were introduced to voice-based AI features, image recognition tools, content generation, and practical business use cases relevant to artisans, tailors, craftspeople, and other traditional occupations covered under the PM Vishwakarma Scheme. The resource persons also emphasized the importance of the responsible and safe use of AI technologies. Participants were advised not to share sensitive personal information, bank account details, passwords, OTPs, or other confidential data while using AI platforms. Beneficiaries were encouraged to use AI tools ethically and responsibly to maximize their benefits. The programme
Jun 1, 2026 · via ladakh.gov.in
Strategic HR Tamil Nadu's HR department to adopt mandatory face-ID attendance from June 1 Tamil Nadu's Human Resource Management Department will begin using a mandatory biometric and facial recognition attendance system from June 1, as the State government seeks to improve punctuality and attendance compliance among employees. The Tamil Nadu government has made biometric and facial recognition-based attendance compulsory for employees of its Human Resource Management Department, introducing a new digital monitoring system aimed at strengthening attendance compliance. The directive will come into force on June 1, 2026, according to an official circular issued by the department. The move follows concerns over employee punctuality and attendance, with Secretariat sources indicating that complaints had been received about some staff members allegedly failing to report to work on time. New attendance protocol combines multiple verification methods According to the circular issued by S. Thankapappa, Deputy Secretary of the Human Resource Management Department, the decision was taken following instructions from the Principal Secretary to the Government. Under the revised system, employees will be required to record their attendance through multiple channels. The circular directs all officers and staff to: - Report to office before 10 am - Mark attendance through the biometric attendance system - Complete face-ID attendance verification - Continue maintaining manual attendance records - Wear official identity cards while on duty The new framework introduces an additional layer of digital verification alongside existing attendance procedures. Department-specific rollout begins on June 1 The order applies to officers and employees working within the Human Resource Management Department. Based on the circular, the measure is currently limited to the department and does not extend to all government departments across Tamil Nadu. The introduction of facial recognition technology marks a notable addition to attendance management practices within the department, combining biometric authentication, face-based verification and
Jun 1, 2026 · via peoplematters.in
Researchers at the ABV-Indian Institute of Information Technology (IIIT), Gwalior, have developed a new artificial intelligence system that combines text analysis, image recognition and fuzzy logic to detect fake news in Indian media with high accuracy. The system, called F2IND-IT! (fuzzy fake Indian news detection using images and text), was described in a recent paper uploaded to arXiv. The researchers say the project addresses a growing challenge in India, where rapid internet penetration and social media use have accelerated the spread of misinformation. According to data from the Press Information Bureau, under the Ministry of Information and Broadcasting, 1,575 fake news cases were reported between 2022 and March 2025. The number rose from 338 in 2022 to 583 in 2024. Data from the National Crime Records Bureau also show a 214 per cent increase in fake news cases during the early pandemic period from 2018 to 2020. A 2024 study by ISB and CyberPeace found that 46 per cent of false information was about politics, and over 77 per cent of it spread through social media platforms. Another survey among Gen Z users in Delhi found that 91 per cent believe fake news can affect election outcomes. To tackle the problem, the researchers designed a multimodal AI model that analyses both the written content of news articles and the accompanying images. The framework uses DistilBERT — a lightweight language-processing model — to understand text semantics, while a convolutional neural network (ResNet-50), which is a deep-learning image recognition system, extracts visual features from photographs. These inputs are then combined using an ‘attention mechanism’ and processed through an adaptive neuro-fuzzy inference system (ANFIS), which produces a probability score indicating whether a news item is fake or genuine. The model was trained and tested on the Indian Fake News Dataset (IFND), which contains
Jun 1, 2026 · via thehindubusinessline.com
Running an optical character recognition (OCR) server might sound like it would need some powerful hardware, like a rack-mounted, water-cooled machine, or at least a nice desktop or laptop. But if you have the time, anything could be used. [Hemant] has a long-running personal project that processes a lot of image data over a long time, and set up the OCR server on an iPhone 8 running entirely with solar power, rather than turn to more typical hardware. Part of what makes this task feasible for low-powered hardware is Apple’s Vision framework, which uses machine learning to aid in things like character recognition (among other tasks). It will run on an iPhone just as easily as a Mac. The phone’s built-in battery already provides the first step of an off-grid setup. This build relies on a separate power bank to integrate the phone with the solar panel more easily. On the software side, [Hemant] reports that the true challenge wasn’t setting up the server as much as it was keeping the iPhone from sleeping or stopping his program from running full-time. A system like this running off-grid, especially considering the costs of the solar panel and power bank, might seem counterproductive. But when comparing electricity costs for running the same software on his server, he estimates he saves about $10 per month with this setup, which has a payback of somewhere around 2-3 years. Not too bad for a phone that would have otherwise ended up in a landfill. Old phones can be surprisingly good choices for servers, too. It helps if they can run Linux, but plenty of phones will support server applications, even when running their native OS. We were doing OCR locally on lame Windows machines 30 years ago, so it’s hardly surprising that it’s still possible.
Jun 1, 2026 · via hackaday.com
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Jun 1, 2026 · via youtube.com
Researchers at the ABV-Indian Institute of Information Technology (IIIT), Gwalior, have developed a new artificial intelligence system that combines text analysis, image recognition and fuzzy logic to detect fake news in Indian media with high accuracy. The system, called F2IND-IT! (fuzzy fake Indian news detection using images and text), was described in a recent paper uploaded to arXiv. The researchers say the project addresses a growing challenge in India, where rapid internet penetration and social media use have accelerated the spread of misinformation. According to data from the Press Information Bureau, under the Ministry of Information and Broadcasting, 1,575 fake news cases were reported between 2022 and March 2025. The number rose from 338 in 2022 to 583 in 2024. Data from the National Crime Records Bureau also show a 214 per cent increase in fake news cases during the early pandemic period from 2018 to 2020. A 2024 study by ISB and CyberPeace found that 46 per cent of false information was about politics, and over 77 per cent of it spread through social media platforms. Another survey among Gen Z users in Delhi found that 91 per cent believe fake news can affect election outcomes. To tackle the problem, the researchers designed a multimodal AI model that analyses both the written content of news articles and the accompanying images. The framework uses DistilBERT — a lightweight language-processing model — to understand text semantics, while a convolutional neural network (ResNet-50), which is a deep-learning image recognition system, extracts visual features from photographs. These inputs are then combined using an ‘attention mechanism’ and processed through an adaptive neuro-fuzzy inference system (ANFIS), which produces a probability score indicating whether a news item is fake or genuine. The model was trained and tested on the Indian Fake News Dataset (IFND), which contains
Jun 1, 2026 · via thehindubusinessline.com
Notre Dame researchers release open-source iris recognition tools built for NIST testing Researchers at the University of Notre Dame have developed a new open-source toolkit intended to make iris recognition technology more transparent, easier to test, and more accessible to academic researchers working outside the commercial biometric industry. The paper, Lowering the Barrier to IREX Participation: Open-Source Algorithms, Toolkit, and Benchmarking for Iris Recognition, presents two new iris recognition algorithms, along with open-source implementations designed to comply with the National Institute of Standards and Technology’s (NIST) Iris Exchange, known as IREX. The work is aimed at a long-standing gap in biometric testing, as NIST’s IREX program has largely evaluated closed-source commercial iris recognition systems rather than open academic tools. The researchers say that matters because iris recognition is increasingly used in security and identity systems, but many of the most capable algorithms remain proprietary, and that limits outside review, makes reproducibility difficult, and leaves researchers without a strong open baseline for comparing new methods. It also creates problems for forensic uses of iris recognition, where explainability and human interpretation can be important. The paper introduces two new neural-network-based methods. The first, called TripletIris, uses a ConvNeXt-tiny model trained with batch-hard triplet loss. In simple terms, the model learns to pull images of the same iris closer together in a mathematical feature space while pushing images of different irises farther apart. The second, called ArcIris, uses a ResNet100 model trained with ArcFace loss, a method designed to create clearer separation between identities. The researchers also created IREX-compliant C++ versions of two existing Notre Dame iris recognition methods. One, HDBIF, uses human saliency-driven filtering to encode iris texture. The other, CRYPTS, detects and compares Fuchs’ crypts, visible structures in the iris that can be useful in human-interpretable forensic analysis. CRYPTS is particularly
Jun 1, 2026 · via biometricupdate.com
Ukraine's Defense Forces have been steadily disrupting russian logistics using drones equipped with advanced AI algorithms, including the Hornet system. That pressure appears to be pushing russian troops toward increasingly unconventional solutions. A photograph recently surfaced online showing a russian military KamAZ truck painted in a highly unusual pattern. At first glance, it resembles an attempt to imitate a zebra's stripes. In reality, it appears to be an effort to recreate so-called dazzle camouflage. Read more: How Many Pantsir Systems Has russia Placed on Moscow Rooftops to Protect Kremlin From Ukrainian Drones Dazzle camouflage was a highly specialized form of naval camouflage developed during World War I. It consisted of large, brightly colored, asymmetrical geometric shapes designed to break up a ship's recognizable outline. A famous 1918 photograph of several Town-class light cruisers demonstrates the effect particularly well. Unlike conventional camouflage, which is intended to conceal an object, dazzle camouflage was designed to make it difficult to accurately determine a target's course, speed, and distance. At the time, these parameters were measured using optical rangefinders. The technique was not limited to black-and-white patterns. It employed multiple colors as well as deliberately distorted light and shadow patterns to confuse observers. The goal was to interfere with both human perception and the operation of optical rangefinding equipment. For example, naval crews often had to align stereoscopic images or estimate a ship's height from the waterline to the top of its mast before identifying its class and calculating its position. Without accurate information on a vessel's type, speed, course, and range, it was impossible to generate reliable firing solutions for naval guns or torpedoes. In other words, dazzle camouflage was specifically designed to disrupt enemy targeting calculations. It could only be effective against large targets observed from considerable distances. Despite several experiments, the
Jun 1, 2026 · via en.defence-ua.com
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May 31, 2026 · via youtube.com
On Tianjin’s streets, patrol officers are slipping on smart glasses that read plates, parse text, and respond to voice, feeding data back in real time. A traffic stop near a school becomes a quick scan, while a patrol can match a lost elder to records in seconds. Officials tout sharper, faster policing, with high recognition rates and first-person design, even if the battery taps out after a couple of hours. Privacy advocates see something else entirely, warning this is one more layer in an expanding surveillance stack that could soon link up with drones and robots. A new tool in Tianjin’s streets On a busy corner in Tianjin, an officer scans the crowd through a new kind of lens. Smart glasses are sliding into daily policing, assisting with patrols, traffic control, and urban management. The promise is speed and precision. The worry is scope. According to China Daily, these devices are already in field use, stitching real-time information directly into an officer’s line of sight. - NASA confirms this giant Chinese dam is slowing Earth’s rotation by microseconds NASA confirms this giant Chinese dam is slowing Earth’s rotation by microseconds - Idris Elba finally answers the Bond question and says he was never in the running Idris Elba finally answers the Bond question and says he was never in the running What these glasses can do The system reads text, obeys voice prompts, and recognizes license plates, feeding back instant lookups from connected databases. For example, an officer can confirm an ID without stepping away or juggling a handheld terminal. That efficiency, impressive on paper, also heightens questions at street level: how much recognition is too much in public spaces, and who sets the guardrails? Practical benefits at work Early anecdotes focus on quick wins. Officers say the glasses helped
May 31, 2026 · via 3dvf.com
- Aviation - 1 min read Digi Yatra crosses 10 crore journeys, set to expand to 27 more airports The app, which uses facial recognition for airport entry and boarding processes, is currently operational at 38 airports across the country. India’s biometric air travel platform Digi Yatra has crossed 10 crore passenger journeys, with more than 2.4 crore downloads across Android and iOS platforms, according to the Ministry of Civil Aviation. The app, which uses facial recognition for airport entry and boarding processes, is currently operational at 38 airports across the country. According to the ministry, Digi Yatra has reduced average passenger processing time at airport entry points from about 15 seconds to 5 seconds by replacing manual document checks. The system is aimed at easing passenger movement and reducing congestion at airport terminals amid rising domestic air traffic. According to the ministry’s statement, the government plans to extend the service to 27 additional airports by next year, including upcoming greenfield airports at Navi Mumbai, Jewar and Bhogapuram. “The scale of Digi Yatra’s adoption comes at a critical juncture. Daily domestic passenger traffic, which averaged below 2 lakh passengers in 2014, has now crossed the 5-lakh mark on numerous occasions over the last three years,” said Ram Mohan Naidu, Minister for Civil Aviation. The platform currently supports 11 languages, with plans underway to add 11 more regional languages by the end of the year. Digi Yatra follows a device-based data storage model, under which passenger information remains encrypted on users’ smartphones and is shared with departure airports for limited-duration identity verification. The government is also deploying other digital tools in aviation operations, including self-baggage drop systems, upgrades to air traffic control automation and AI-based airport management systems. Comments All Comments By commenting, you agree to the Prohibited Content Policy PostBy
May 31, 2026 · via infra.economictimes.indiatimes.com
PARIS, France — Two humpback whales have set new records for the longest-known distances travelled for their species by embarking on a journey of over 14,000 kilometres between Brazil and Australia, scientists said Wednesday. The international team of researchers were able to piece together the separate odysseys from photos of the whales’ tails — including some taken by amateur photographers on cruises — captured decades apart. These journeys through open water are “something that had never been documented before”, Cristina Castro, a marine biologist at the Pacific Whale Foundation in Ecuador, told AFP. “It’s not unheard of for an individual to occasionally stray (from a migratory route), but what we documented here goes far beyond that,” added the lead author of a new study in Royal Society Open Science. Every humpback has a pattern on the underside of their tail — or fluke — that is unique “like a human fingerprint”, Castro said. The scientists analyzed more than 19,000 photos taken between 1984 and 2005 in eastern Australia and Latin America using an image recognition algorithm. Then they sifted through each potential match to trace the two whales’ journey across the world. The first humpback was initially photographed in 2007 in Hervey Bay, in the state of Queensland on Australia’s east coast. It was spotted at the same place again in 2013. Its unique fluke next popped up six years later — this time off the coast of the Brazilian megacity Sao Paulo. As the crow flies, this is a distance of around 14,200 km (8,800 miles). Because the scientists only know the start and end points of the journey, it was impossible to determine the whale’s exact route -- or how far it actually travelled. The second whale made the opposite journey. First it was photographed off the coast
May 30, 2026 · via cp24.com
Biometrics is not a new concept, but its use by the Transportation Security Administration (TSA) across an increasing number of airports in the United States is causing mixed reactions. Facial recognition software is becoming the norm at many major U.S. airports (more than 250 so far, according to the TSA, with more on the way), and not every traveler is on board. The signs alerting passengers to the TSA's biometric scan are, apparently, unclear, causing confusion and distrust among frequent travelers in some cases. Airport security can be stressful in itself, and now both TSA employees and travelers are sharing the same complaints about the use of somewhat invasive scans, the way they're communicated, and the process of opting out and not being allowed to (which, in 2025, sparked a whole investigation into the TSA by Congress). Facial Scan Signs At Hundreds Of U.S. Airports Create A Pattern Of Complaints The opinions about facial recognition software are overwhelmingly mixed. Even so, pressure from lawmakers is causing TSA and the U.S. Department of Homeland Security (DHS) to update airport technology, and biometrics seems to be the answer. To communicate this gradually rolling-out addition at airports, passengers are increasingly seeing signs pop up at TSA checkpoints, which indicate that facial recognition is in process—but that passengers can also opt out if they so desire. Therein lies travelers', as well as some TSA employees', pattern of complaints; reportedly, those signs cause some confusion on both sides. One TSA officer said that passengers often hand over their ID and avoid the camera, without informing them that they want to opt out of the facial scan. "The most consistently annoying thing is people just assuming we know they want to opt out. Just walk up and say, 'I’d like to opt out of the photo,'"
May 30, 2026 · via thetravel.com
| Getting your Trinity Audio player ready... | This series was produced in partnership with the Pulitzer Center’s Artificial Intelligence (AI) fellowship. Following the 1999–2001 Kosovo crisis, Microsoft, in collaboration with Hewlett-Packard and Compaq, provided the United Nations High Commission for Refugees (UNHCR) with hardware and software to support a refugee mobile registration scheme that later informed the development of Project Profile. In 2002, the UNHCR launched Project Profile after its governing body, the Executive Committee of the High Commissioner’s Programme (ExCom), encouraged the standardisation of registration guidelines and the introduction of “new techniques and tools, including biometrics” as well as global software such as the UNHCR’s Profile Global Registration System (proGres). Microsoft provided technical advice and guidance on the technology specifications. The Elca Group, a Swiss company, won the tender to develop the global proGres database as part of Project Profile B. Elca was responsible for the development of the three versions of proGres (V1-V3), the UNHCR told vendors in 2013. Elca did not respond to a request for comment. According to various agency news briefs, the UNHCR and volunteers from Microsoft trained staff to use proGres, then primarily a registration tool for capturing biographical data and facial photographs, and helped set up the registration systems in several countries. The UNHCR did not provide a comment on who specifically deployed proGres, including in Kenya in 2004. proGres is built on Microsoft Dynamic Customer Relationship Management (CRM) software and is the backbone of the UNHCR’s operations, including registration, Refugee Determination Status (RSD), resettlement, and repatriation. “Thanks for checking in. The company has nothing to share,” was Microsoft’s response to The Elephant through its long-term partner We. Communications, a public relations and integrated marketing agency. A 2019 UN financial audit report states that proGres V3, an offline system of separate databases
May 30, 2026 · via theelephant.info