Fire & Emergency Services
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Autonomous firefighting robot can drive straight into a 1,000 degree blaze
The tank-like vehicle is already being tested in South Korea. The robot sprays itself with water to stay cool and uses thermal cameras to see through smoke. Breakthroughs, discoveries, and DIY tips sent six days a week. Firefighters in South Korea will soon start deploying alongside a massive, six-wheeled, self-cooling autonomous robot that could help keep them safe. Hyundai recently revealed the new, driverless ground drone, built atop a chassis initially intended for military use and looking like something out of a sci-fi film.
- Asia > South Korea (0.84)
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- North America > United States > California > Los Angeles County > Los Angeles (0.05)
2,500-year-old settlement found during fire station construction
The tree cover marks the course of the source stream, which formed the basis for the construction of the former farmstead. Breakthroughs, discoveries, and DIY tips sent six days a week. While a recent Iron Age discovery in northern Germany is proving itself an archaeological goldmine, local firefighters might be a bit annoyed by the find. According to the Regional Association of Westphalia-Lippe (LWL), construction on a new fire station in the town of Hüllhorst roughly 45 miles west of Hanover was delayed after the surveyors identified evidence of a settlement dating back over 2,500 years. As only the third such find in the region, the site offers an exceptional opportunity to learn more about ancient life in Germany prior to the Roman Empire's arrival in 1st century BCE.
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VastTrack: Vast Category Visual Object Tracking
V astTrack consists of a few attractive properties: (1) V ast Object Category . In particular, it covers targets from 2,115 categories, significantly surpassing object classes of existing popular benchmarks ( e.g ., GOT -10k with 563 classes and LaSOT with 70 categories). Through providing such vast object classes, we expect to learn more general object tracking.
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Greece biscuit factory fire leaves at least three dead
At least three people have been killed and two others are still missing after a fire broke out at a food factory near the central Greek city of Trikala, officials say. The blaze began in the early hours of Monday at a Violanta biscuit factory, where 13 workers were on site, according to local media. Eight people managed to escape, while firefighters later recovered three bodies from the building. Drone footage showed thick smoke billowing from the fire. A powerful explosion was reportedly heard before it broke out but an investigation into the cause of the blaze is ongoing.
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New LAFD chief won't look into who watered down Palisades fire report
Things to Do in L.A. Tap to enable a layout that focuses on the article. New LAFD chief won't look into who watered down Palisades fire report Deputy Chief Jaime Moore fields questions from city council members before being confirmed as the new LAFD chief after a unanimous vote by the L.A. City Council on Nov. 14. This is read by an automated voice. Please report any issues or inconsistencies here . LAFD Chief Jaime Moore said he is taking a forward-looking approach and not seeking to assign blame for changes to the report.
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Day of mourning for bar fire victims in Switzerland
A day of national mourning is being held in Switzerland on Friday, following a fire which killed 40 young people, mostly teenagers, in a bar in the Crans-Montana ski resort on New Year's Eve. Church bells rang across the country for five minutes, and people stood for a minute's silence in their memory. Firefighters in the resort were applauded as they joined an audience watching the tribute ceremony, which was live-streamed to Crans-Montana from the Swiss city of Martigny. The ceremony saw the leaders of neighbouring countries, including France's Emmanuel Macron, join an audience while speakers, including the Valais canton's president, paid tribute to those who died. The annual food fight festival ''Els Enfarinats'' has left the Spanish town of Ibi covered in flour and egg shells.
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Predicting the Containment Time of California Wildfires Using Machine Learning
California's wildfire season keeps getting worse over the years, overwhelming the emergency response teams. These fires cause massive destruction to both property and human life. Because of these reasons, there's a growing need for accurate and practical predictions that can help assist with resources allocation for the Wildfire managers or the response teams. In this research, we built machine learning models to predict the number of days it will require to fully contain a wildfire in California. Here, we addressed an important gap in the current literature. Most prior research has concentrated on wildfire risk or how fires spread, and the few that examine the duration typically predict it in broader categories rather than a continuous measure. This research treats the wildfire duration prediction as a regression task, which allows for more detailed and precise forecasts rather than just the broader categorical predictions used in prior work. We built the models by combining three publicly available datasets from California Department of Forestry and Fire Protection's Fire and Resource Assessment Program (FRAP). This study compared the performance of baseline ensemble regressor, Random Forest and XGBoost, with a Long Short-Term Memory (LSTM) neural network. The results show that the XGBoost model slightly outperforms the Random Forest model, likely due to its superior handling of static features in the dataset. The LSTM model, on the other hand, performed worse than the ensemble models because the dataset lacked temporal features. Overall, this study shows that, depending on the feature availability, Wildfire managers or Fire management authorities can select the most appropriate model to accurately predict wildfire containment duration and allocate resources effectively.
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Ukraine firefighters rush to rescue people, pets after Russian strike
What is in the 28-point US plan for Ukraine? 'Ukraine is running out of men, money and time' Can the US get all sides to end the war? Why is Europe opposing Trump's peace plan? Firefighters evacuated residents and their pets from a nine-storey apartment building in Ukraine's Sumy region after a Russian drone strike. The strikes come as Ukrainian President Volodymyr Zelenskyy met with leaders of the UK, France and Germany in London to discuss the US peace plan.
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Binary Decision Process in Pre-Evacuation Behavior
Wang, Peng N., Luh, Peter B., Lu, Xuesong, Sincak, Peter, Pitukova, Laura
In crowd evacuation the time interval before decisive movement towards a safe place is defined as the pre-evacuation phase, and it has crucial impact on the total time required for safe egress. This process mainly refers to situation awareness and response to an external stressors, e.g., fire alarms. Due to the complexity of human cognitive process, simulation is used to study this important time interval. In this paper a binary decision process is formulated to simulate pre-evacuation time of many evacuees in a given social context. The model combines the classic opinion dynamics (the French-DeGroot model) with binary phase transition to describe how group pre-evacuation time emerges from individual interaction. The model parameters are quantitatively meaningful to human factors research within socio-psychological background, e.g., whether an individual is stubborn or open-minded, or what kind of the social topology exists among the individuals and how it matters in aggregating individuals into social groups. The modeling framework also describes collective motion of many evacuee agents in a planar space, and the resulting multi-agent system is partly similar to the Vicsek flocking model, and it is meaningful to explore complex social behavior during phase transition of a non-equilibrium process.
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