surveillance camera
You Can Now Destroy Flock Cameras for Cash in GTA V
A new mod lets you smash and shoot Flock's automatic license plate readers around the fictional Los Santos. People are not happy about Flock Safety's automated license plate readers and the cops that allegedly misuse them . If you're one of those ALPR-haters, you can now take out your rage in the video game by installing Grand Theft Automated License Plate Reader, a mod built by artist Morry Kolman. Players can smash and shoot down the cameras and get paid $600 for each one they destroy, which Kolman priced based on a teardown of a Flock Falcon Flex Camera by the Iowa-based civil liberties group Eyes Off of Cedar Rapids. The in-game cameras log every time a player destroys and drives by one, and players can render a photo album of their interactions.
The Logical End Point of AI Job Interviews Is Two Bots Talking to Each Other
Christopher was sick of being ghosted by AI recruiters. So he unleashed ChatGPT on his robot interviewer. Christopher has become accustomed to jumping through the endless hoops of the modern job hunt. Like many government contractors, his work has dried up in the DOGE era . Over the past six months, he has applied to roughly 700 jobs; in the vast majority of cases, he's heard nothing back.
I Spy with My Little Eye . . . a Spy
Atlanta has more street cameras per capita than anywhere outside of China. On a walking tour of the city, can anti-surveillance vigilantes spot--and dodge--them all? Austin Kral and Ed Vogel stood in a downtown Atlanta park the other day, preparing to lead what they'd advertised on flyers as a "spy hunt." The spies were the surveillance cameras used by police and the government, "and the corporate vender ecosystem," Vogel said. He had on a black ball cap and a T-shirt that read " = ."
Revolutionizing Traffic Management with AI-Powered Machine Vision: A Step Toward Smart Cities
DolatAbadi, Seyed Hossein Hosseini, Hashemi, Sayyed Mohammad Hossein, Hosseini, Mohammad, AliHosseini, Moein-Aldin
The rapid urbanization of cities and increasing vehicular congestion have posed significant challenges to traffic management and safety. This study explores the transformative potential of artificial intelligence (AI) and machine vision technologies in revolutionizing traffic systems. By leveraging advanced surveillance cameras and deep learning algorithms, this research proposes a system for real-time detection of vehicles, traffic anomalies, and driver behaviors. The system integrates geospatial and weather data to adapt dynamically to environmental conditions, ensuring robust performance in diverse scenarios. Using YOLOv8 and YOLOv11 models, the study achieves high accuracy in vehicle detection and anomaly recognition, optimizing traffic flow and enhancing road safety. These findings contribute to the development of intelligent traffic management solutions and align with the vision of creating smart cities with sustainable and efficient urban infrastructure.
Whistleblowers claim Border Patrol surveillance cameras 'out of service' as GOP demands answers from DHS
Fox News host Sean Hannity calls out Vice President Kamala Harris' far-left policies ahead of the November election on'Hannity.' Over the last year, Fox News correspondents Bill Melguin and Griff Jenkins have been following complaints from Border Patrol sources that many of the crucial remote surveillance cameras in multiple sectors along the southern border have not been operational. U.S. House of Representatives Homeland Security Committee Republicans say whistleblowers came forward to the committee last week, claiming that "some of the busiest Southwest border sectors have nearly 50 or more cameras offline with multiple towers that have been out of service for more than a year." On Wednesday, the House Homeland Security Committee sent a letter to Department of Homeland Security (DHS) Secretary Alejandro Mayorkas, claiming that whistleblowers came forward to the committee last week with concerning information on this issue. The letter from Republicans to Mayorkas demanded answers.
Long-Range Biometric Identification in Real World Scenarios: A Comprehensive Evaluation Framework Based on Missions
Aykac, Deniz, Brogan, Joel, Barber, Nell, Shivers, Ryan, Zhang, Bob, Sacca, Dallas, Tipton, Ryan, Jager, Gavin, Garret, Austin, Love, Matthew, Goddard, Jim, Cornett, David III, Bolme, David S.
The considerable body of data available for evaluating biometric recognition systems in Research and Development (R\&D) environments has contributed to the increasingly common problem of target performance mismatch. Biometric algorithms are frequently tested against data that may not reflect the real world applications they target. From a Testing and Evaluation (T\&E) standpoint, this domain mismatch causes difficulty assessing when improvements in State-of-the-Art (SOTA) research actually translate to improved applied outcomes. This problem can be addressed with thoughtful preparation of data and experimental methods to reflect specific use-cases and scenarios. To that end, this paper evaluates research solutions for identifying individuals at ranges and altitudes, which could support various application areas such as counterterrorism, protection of critical infrastructure facilities, military force protection, and border security. We address challenges including image quality issues and reliance on face recognition as the sole biometric modality. By fusing face and body features, we propose developing robust biometric systems for effective long-range identification from both the ground and steep pitch angles. Preliminary results show promising progress in whole-body recognition. This paper presents these early findings and discusses potential future directions for advancing long-range biometric identification systems based on mission-driven metrics.
North Korea to put Chinese surveillance cameras in schools and workplaces to monitor citizens, report says
Fox News correspondent Stephanie Bennett joins'Fox News Live' to break down recent evidence tying missile fragments in Russian attacks to North Korea. North Korea is putting surveillance cameras in schools and workplaces and collecting fingerprints, photographs and other biometric information from its citizens in a technology-driven push to monitor its population even more closely, a report said Tuesday. The state's growing use of digital surveillance tools, which combine equipment imported from China with domestically developed software, threatens to erase many of the small spaces North Koreans have left to engage in private business activities, access foreign media and secretly criticize their government, the researchers wrote. But the isolated country's digital ambitions have to contend with poor electricity supplies and low network connectivity. Those challenges, and a history of reliance on human methods of spying on its citizens, mean that digital surveillance isn't yet as pervasive as in China, according to the report, published by the North Korea-focused website 38 North. The study's findings align with widely held views that North Korean leader Kim Jong Un is stepping up efforts to tighten the state's control of its citizens and promote loyalty to his regime.
RAG-Fusion: a New Take on Retrieval-Augmented Generation
Infineon has identified a need for engineers, account managers, and customers to rapidly obtain product information. This problem is traditionally addressed with retrieval-augmented generation (RAG) chatbots, but in this study, I evaluated the use of the newly popularized RAG-Fusion method. RAG-Fusion combines RAG and reciprocal rank fusion (RRF) by generating multiple queries, reranking them with reciprocal scores and fusing the documents and scores. Through manually evaluating answers on accuracy, relevance, and comprehensiveness, I found that RAG-Fusion was able to provide accurate and comprehensive answers due to the generated queries contextualizing the original query from various perspectives. However, some answers strayed off topic when the generated queries' relevance to the original query is insufficient. This research marks significant progress in artificial intelligence (AI) and natural language processing (NLP) applications and demonstrates transformations in a global and multi-industry context.