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AI system detects fires before alarms sound, NYU study shows

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NYU research introduces video-based fire detection

The NYU Tandon School of Engineering has reported that its Fire Research Group has developed an artificial intelligence system that can detect fires and smoke in real time using existing CCTV cameras.

According to NYU Tandon, the system analyses video frames within 0.016 seconds, faster than a human blink, and provides immediate alerts.

The researchers explained that conventional smoke alarms activate only once smoke has reached a sensor, whereas video analysis can recognise fire at an earlier stage.

Lead researcher Prabodh Panindre, Research Associate Professor at NYU Tandon’s Department of Mechanical and Aerospace Engineering, said: “The key advantage is speed and coverage.

“A single camera can monitor a much larger area than traditional detectors, and we can spot fires in the initial stages before they generate enough smoke to trigger conventional systems.”

Ensemble AI approach improves accuracy

NYU Tandon explained that the system combines multiple AI models rather than relying on a single network.

It noted that this reduces the risk of false positives, such as mistaking a bright object for fire, and improves detection reliability across different environments.

The team reported that Scaled-YOLOv4 and EfficientDet models provided the best results, with detection accuracy rates above 78% and processing times under 0.02 seconds per frame.

By contrast, Faster-RCNN produced slower results and lower accuracy, making it less suitable for real-time IoT use.

Dataset covers all NFPA fire classes

According to the NYU researchers, the system was trained on a custom dataset of more than 7,500 annotated images covering all five fire classes defined by the National Fire Protection Association.

The dataset included Class A through K fires, with scenarios ranging from wildfires to cooking incidents.

This approach allowed the AI to generalise across different ignition types, smoke colours, and fire growth patterns.

The team explained that bounding box tracking across frames helped differentiate live flames from static fire-like objects, achieving 92.6% accuracy in reducing false alarms.

Professor Sunil Kumar of NYU Abu Dhabi said: “Real fires are dynamic, growing and changing shape.

“Our system tracks these changes over time, achieving 92.6% accuracy in eliminating false detections.”

Technical evaluation of detection models

NYU Tandon reported that it tested three leading object detection approaches: YOLO, EfficientDet and Faster-RCNN.

The group found that Scaled-YOLOv4 achieved the highest accuracy at 80.6% with an average detection time of 0.016 seconds per frame.

EfficientDet-D2 achieved 78.1% accuracy with a slightly slower response of 0.019 seconds per frame.

Faster-RCNN produced 67.8% accuracy and required 0.054 seconds per frame, making it less practical for high-throughput applications.

The researchers concluded that Scaled-YOLOv4 and EfficientDet-D2 offered the best balance of speed and reliability for real-world deployment.

Dataset preparation and training methods

The research team stated that it collected approximately 13,000 images, which were reduced to 7,545 after cleaning and annotation.

Each image was labelled with bounding boxes for fire and smoke, and the dataset was evenly distributed across the five NFPA fire classes.

The models were pre-trained on the Common Objects in Context dataset before being fine-tuned on the fire dataset for hundreds of training epochs.

The team confirmed that anchor box calibration and hyperparameter tuning further improved YOLO model accuracy.

They reported that Scaled-YOLOv4 with custom training configurations provided the best results for dynamic fire detection.

IoT cloud-based deployment

The researchers outlined that the system operates in a three-layer Internet of Things architecture.

CCTV cameras stream raw video to cloud servers where AI models analyse frames, confirm detections and send alerts.

Detection results trigger email and text notifications, including short video clips, using Amazon Web Services tools.

The group reported that the system processes frames in 0.022 seconds on average when both models confirm a fire or smoke event.

This design, they said, allows the system to run on existing “dumb” CCTV cameras without requiring new hardware.

Deployment framework and false alarm reduction

The NYU team explained that fire detections are validated only when both AI models agree and the bounding box area grows over time.

This approach distinguishes real flames from static images of fire, preventing common sources of false alerts.

The deployment is based on Amazon Web Services with EC2 instances handling video ingestion and GPU-based inference.

Results and metadata are stored in S3 buckets and notifications are sent through AWS SNS and SES channels.

The researchers stated that this cloud-based framework ensures scalability and consistency across multiple camera networks.

Applications in firefighting and wildland response

NYU Tandon stated that the technology could be integrated into firefighting equipment, such as helmet-mounted cameras, vehicle cameras and autonomous robots.

It added that drones equipped with the system could provide 360-degree views during incidents, assisting fire services in locating fires in high-rise buildings or remote areas.

Capt. John Ceriello of the Fire Department of New York City said: “It can remotely assist us in confirming the location of the fire and possibility of trapped occupants.”

The researchers noted that the system could also support early wildfire detection, giving incident commanders more time to organise resources and evacuations.

Broader safety applications

Beyond fire detection, the NYU group explained that the same AI framework could be adapted for other safety scenarios, including medical emergencies and security threats.

It reported that the ensemble detection and IoT architecture provide a model for monitoring and alerting in multiple risk environments.

Relevance for fire and safety professionals

For fire and rescue services, the system demonstrates how existing CCTV infrastructure can be adapted for early fire detection without requiring new sensors.

For building managers, the research shows how AI video analysis could supplement or back up smoke alarms, particularly in settings where detector failure is a risk.

For wildland and urban response teams, the ability to embed the system into drones or helmet cameras may improve situational awareness and decision-making during fast-developing incidents.

AI system uses CCTV to detect fires in real time: Summary

The NYU Tandon School of Engineering Fire Research Group has reported an AI system that detects fires using CCTV cameras.

The research was published in the IEEE Internet of Things Journal.

The system processes video at 0.016 seconds per frame.

Scaled-YOLOv4 achieved 80.6% accuracy and EfficientDet achieved 78.1% accuracy.

False detections were reduced by tracking bounding box changes over time.

The dataset included 7,545 images covering all five NFPA fire classes.

Alerts are generated in real time through AWS cloud systems.

Applications include CCTV monitoring, drones, firefighter equipment and wildland detection.

The research suggests the same framework could support wider emergency monitoring.



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UK to receive $6.8B Google investment for AI development

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Google, part of Alphabet Inc., revealed its intention to invest £5 billion, approximately $6.8 billion, in the UK specifically to boost the development of an AI economy in the country in the next two years.

The tech giant shared this significant plan just as the US President Donald Trump gets ready to disclose economic deals surpassing $10 billion. This was brought during Trump’s visit to the US’s long-standing ally this week.

Google and AI rivals fuel UK tech surge

Not all the investment will be dedicated to the above sector; some will be set aside for a newly developed data center in Waltham Cross that focuses on meeting the surging demand for Google’s services, such as map and search services. According to the tech giant, this investment is a game-changer that will create about 8,250 jobs for UK citizens annually.

Just like Google, its rivals in the AI race, OpenAI and Nvidia, are also eyeing the UK to make investments worth billions in the country’s data centers during Trump’s visit.

According to reports, the investment will be implemented in collaboration with Nscale Global Holdings Ltd. Nscale is a London firm that operates large scale data centers and is a major player in Europe’s growing demand for AI infrastructure.

Trump’s visit to the UK strengthens the economies of the two nations 

Earlier on September 15, senior officials in the US revealed that the American president was planning to announce economic deals exceeding $10 billion during his second visit to the United Kingdom.

“The trip to the U.K. is going to be incredible,” Trump told reporters Sunday. He said Windsor Castle is “supposed to be amazing” and added: “It’s going to be very exciting.”

The visit will feature a collaboration in science and technology, a sector anticipated to bring billions in new investments. The officials who shared these details about Trump’s trip wished to remain anonymous due to the confidential nature of the discussion.

They also stated that there is a likelihood that Trump and Keir Starmer, UK’s Prime Minister, might announce a defense technology cooperation deal and boost relationships between major financial centers in the two countries.

Some of these economic deals may be announced during a business reception that Rachel Reeves, the Chancellor of the Exchequer, will host, where the two leaders will be present. Other top US tech executives attending the event include Jensen Huang from Nvidia, and Sam Altman from OpenAI. They will participate in roundtable talks on Thursday, September 18, at Chequers, the prime minister’s residence. 

These economic programs came alongside previous efforts to sign a significant deal that would ease the construction of nuclear power plants. The two countries will utilize each other’s safety checks on reactor designs that will accelerate the approval process.

Even though some economic deals are progressing smoothly, US officials have highlighted that Trump’s announcements will likely not include a deal to loosen US tariff policies on scotch whiskey. Notably, this is what Starmer has been actively pushing for.

The officials also pointed out a likelihood that the announcements will not address Trump’s ongoing worries brought about by the UK government’s ability to regulate US-based tech firms such as Apple and Alphabet, in connection with their control over smartphones.

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Researchers used AI to design the perfect phishing plot, what happened next shocked everyone

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AI is increasingly being put to the test for its potential benefits, but a new experiment has shown how the same technology can also fuel online crime. A Reuters investigation, conducted in partnership with Harvard researcher Fred Heiding, has revealed that some of the world’s most widely used AI chatbots can be nudged into producing scam emails aimed at senior citizens.

In a controlled study, emails generated by these bots were sent to more than 100 elderly volunteers in the United States. While no money or personal data was taken, the results were troubling. About 11 per cent of the participants clicked on the links inside the phishing emails, suggesting that AI-generated scams can be as persuasive as those crafted by humans.

The fake charity experiment with Grok

The investigation began with a test on Grok, the chatbot developed by Elon Musk’s company xAI. Reporters asked it to create a message for older readers about a charity called the “Silver Hearts Foundation”. The mail looked convincing, speaking about dignity for seniors and urging them to join the mission. Without further prompting, Grok even added a line to create urgency: “Click now to act before it’s too late.” The charity did not exist, the entire email was designed to trick recipients.

Phishing: a growing global threat

Phishing, where people are deceived into revealing sensitive information or sending money, is one of the biggest challenges in cybersecurity. According to FBI figures, it is the most reported cybercrime in the US, and older people are among the worst affected. In 2023 alone, Americans over 60 lost nearly $5 billion to such fraud. The agency has also warned that generative AI tools can make these scams more effective and harder to detect.

Chatbots tested beyond Grok

The Reuters team went beyond Grok and tested five other major chatbots – OpenAI’s ChatGPT, Meta’s AI assistant, Google’s Gemini, Anthropic’s Claude and DeepSeek. Initially, most of them refused to generate phishing content. But with slight changes in the way requests were worded, such as describing the exercise as academic research or fiction writing, the chatbots eventually produced scam-like drafts.

Why AI makes scams easier

Heiding, who has studied phishing techniques for years, said this flexibility makes chatbots “potentially valuable partners in crime”. Unlike humans, they can generate dozens of variations instantly, helping criminals cut costs and scale up operations. In fact, Heiding’s earlier research showed that phishing emails written by AI could be just as effective in luring targets as those created manually.

When tested on seniors, five out of nine AI-generated mails resulted in clicks. Two came from Grok, two from Meta AI and one from Claude. None of the volunteers responded to ChatGPT or DeepSeek’s drafts. But the study was not intended to rank which chatbot is more dangerous, rather to show that several can be exploited for scams.

Tech firms acknowledge risks

Technology companies have acknowledged the concerns. Meta said it invests in safeguards to prevent misuse and regularly stress-tests its systems. Anthropic stated that using its chatbot Claude for scams violates its policies and accounts found misusing the tool are suspended. Google said it retrained Gemini after learning it had generated phishing content, while OpenAI has publicly admitted in past reports that its models can be misused for “social engineering”.

Security experts believe the issue lies in how companies balance user experience with safety. Chatbots are designed to be helpful, but stricter refusals could drive users towards rival products with fewer restrictions. This trade-off, researchers argue, creates room for misuse.

The problem is not confined to experiments. Survivors of scam operations in Southeast Asia told Reuters that they had been forced to use ChatGPT in real-world fraud schemes. Workers at such centres reportedly used the bot to polish responses, translate messages and build trust with victims.

Governments and regulators respond

Governments are beginning to take note. Some US states have passed laws against AI-generated fraud, though most target scammers themselves rather than the companies providing the technology. The FBI, in a recent alert, said criminals are now able to “commit fraud on a larger scale” because AI reduces the time and effort required to make scams believable.

– Ends

Published By:

Ankita Garg

Published On:

Sep 16, 2025



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SEERai™ by Galorath Wins SiliconANGLE TechForward Award with Industry-First Agentic Artificial Intelligence

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SEERai Recognized as the Industry’s First Agentic AI Platform Transforming Cost, Schedule, and Risk Planning in Secure Enterprise Environments

LONG BEACH, Calif., Sept. 16, 2025 /PRNewswire/ — Galorath, the premier AI-powered operational intelligence platform provider, today announced that SEERai™ has been named a winner in SiliconANGLE’s 2025 TechForward Awards. The platform was recognized in the “AI Tech – Generative AI & Foundation Models” category for its impact in enabling secure, explainable AI-driven planning across complex programs.

SEERai is the first commercially available agentic AI platform engineered for program-critical outcomes. Unlike generic AI copilots or disconnected estimation tools, SEERai uses a modular architecture of purpose-built agents, retrieval-augmented generation (RAG), and structured decision logic to deliver fully traceable outputs. It enables organizations to accelerate proposal timelines, standardize estimation practices, and scale expert insight—without compromising accuracy, auditability, or security.

“Being recognized by SiliconANGLE is a testament to Galorath’s ongoing commitment to innovation and impact,” said Charles Orlando, Chief Strategy Officer, Galorath Incorporated. “With rising costs, constrained budgets, and outdated tools testing the limits of traditional project planning, SEERai delivers an agentic AI solution that replaces static assumptions with accuracy, agility, and confidence.”

The TechForward Awards recognize the technologies and solutions driving business forward. As the trusted voice of enterprise and emerging tech, SiliconANGLE applies a rigorous editorial lens to highlight innovations reshaping how businesses operate in our rapidly changing landscape. As organizations face pressures to deliver projects faster, reduce costs, and improve outcomes across increasingly complex environments, traditional tools and approaches often fail to adapt to real-time changes, leaving teams struggling with inefficiencies, risks, and misalignment. Galorath’s award-winning SEERai solution is pioneering the future of AI for cost estimation, project planning, and risk management.

“These winners represent the most impressive achievements emerging from today’s fiercely competitive tech landscape, embodying the relentless drive and visionary thinking that pushes entire industries forward,” said John Furrier, co-founder and co-CEO of SiliconANGLE Media. “These are the solutions that business leaders trust to solve their most critical challenges. They’re not just products, they’re competitive advantages.”

The TechForward awards program honors both established enterprise solutions and breakthrough technologies defining the future of business, spanning AI innovation, security excellence, cloud transformation, data platform evolution and blockchain/crypto tech. SEERai was selected from a competitive field of nominees by a panel of industry experts and technology leaders. The complete list of winners can be found online at https://siliconangle.com/awards/.

About SiliconANGLE Media
SiliconANGLE Media is a recognized leader in digital media innovation, bringing together cutting-edge technology, influential content, strategic insights and real-time audience engagement. As the parent company of SiliconANGLE, theCUBE Network, theCUBE Research, CUBE365, theCUBE AI and theCUBE SuperStudios — such as those established in Silicon Valley and the New York Stock Exchange (NYSE) — SiliconANGLE Media transforms the way technology companies connect with their target markets. Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a powerful ecosystem of industry-leading digital media brands, with a reach of 10+ million elite tech professionals, 4+ million SiliconANGLE readers and 250,000+ social media subscribers. The company’s new, proprietary theCUBE AI LLM is breaking ground in audience interaction, leveraging CUBE365’s neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.

About SEER® and SEERai
Galorath’s flagship project estimating software, SEER®, offers unparalleled capabilities in project cost forecasting, risk mitigation, and actionable insights, making it the go-to platform for project cost planning for hardware and software development, systems engineering, aerospace, and manufacturing companies. SEERai is Galorath’s modular agentic AI platform for estimation, sourcing, labor, schedule, and risk, standing out as a first-of-its-kind generative AI for digital engineering support. Combining its connection with the knowledge bases of SEER, along with secure, isolated integration of an organization’s backend systems, processes, databases, and projects, SEERai allows cost and project estimation professionals to use natural language to instantly generate actionable information and data for project and cost estimation, from Work Breakdown Structures (WBS) to project and cost estimation guidance and much more. For more information, visit https://galorath.com/ai.

About Galorath Incorporated
Leveraging four decades of in-market experience and success, Galorath transforms cost, scheduling, should-cost analysis, and project estimation, optimizing outcomes and achieving unparalleled efficiencies for public and private sector organizations worldwide. SEER®, Galorath’s flagship digital engineering platform, is trusted by industry giants like Accenture, NASA, Boeing, the U.S. Department of Defense, and BAE Systems (EU). SEER accelerates time to market, dramatically enhances project predictability and visibility, and ensures project costs are on track and on budget. For more information, visit https://galorath.com/.

All trademarks are the property of their respective owners.

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