Investigadores de la Universidad de Edimburgo han desarrollado una tecnolog\u00eda que empleando IA en sus cascos y equipamiento, podr\u00eda ayudar a los bomberos a mapear m\u00e1s r\u00e1pidamente su entorno, desplazarse en entornos peligrosos y llevar a las personas a un lugar seguro. Estos sistemas fueron exhibidos\u00a0el 28set22, como parte de la inauguraci\u00f3n oficial del\u00a0National Robotarium realizado en esa ciudad.<\/p>\n
Researchers at the University of Edinburgh have developed a technology that could help firefighters more quickly map their surroundings, navigate hazardous environments and get people to safety, which will<\/span>\u00a0be showcased as part of the official opening of the\u00a0National Robotarium<\/a>\u00a0on Wednesday.<\/span><\/p>\n The device uses artificial intelligence (AI) to combine data from thermal-imaging cameras, radar and other sensors mounted on standard-issue fire helmets, giving firefighters real-time information from fire scenes. The entire sensor rig weighs less than one kilogram and uses affordable, off-the-shelf parts that are easy to fit onto standard-issue fire helmets.<\/span><\/p>\n It is hoped the technology could help emergency services more safely navigate dangerous or low-visibility conditions and reduce the time it takes to rescue victims.<\/span><\/p>\n \u201cFirefighters often operate in environments with very low or no visibility due to the vast amount of smoke released from a fire,\u201d said Dr Chris Lu, who is leading the project. \u201cThis can make detecting the location of potential victims and the whereabouts of firefighters very challenging in situations that are often extremely time-sensitive.<\/span><\/p>\n \u201cThis new technology has the potential to support on-the-ground firefighters and scene commanders to make crucial in-the-moment decisions that can enhance search rescue efficiency, ensure safer collaboration between teammates and, most importantly, improve outcomes for potential victims of fire scenes.\u201d<\/span><\/p>\n Field trials of the new technology have been conducted with members of the Scottish Fire and Rescue Service at their \u00a310.5m training facility in Newbridge, Edinburgh.<\/span><\/p>\n \u201cWe are proud that our staff at our Newbridge Training Centre have been able to support with the trialling of this technology,\u201d said Bryan Todd, group commander in training, safety and Assurance at Scottish Fire and Rescue Service.<\/p>\n \u201cSafety, teamwork and innovation are three of our core values as a service and we always welcome opportunities to work in partnership with higher-education organisations and the fantastic work they do in exploring ideas to improve community and firefighter safety.\u201d<\/p>\n The launch of the AI fire helmet technology comes as the National Robotarium\u2019s new \u00a322.4m facility officially opens its doors.\u00a0<\/span>The new facility \u2013 part of the Data-Driven Innovation (DDI) initiative \u2013 is supported by \u00a321m from the UK government and \u00a31.4m from the Scottish government.<\/span><\/p>\n The DDI initiative forms part of the wider \u00a31.3bn Edinburgh and South-East Scotland City Region Deal, which aims to establish Edinburgh as the data capital of Europe.<\/span><\/p>\n The team at the University of Edinburgh aims to develop the technology further to give the helmet the ability to create 3D maps and to provide wearers with a built-in display screen.<\/span><\/p>\n In recent years, several key technological innovations have been developed to protect firefighters and support them in their dangerous mission. Last month,\u00a0a team of scientists from the US National Institute of Standards and Technology and the Hong Kong Polytechnic University developed an AI model to\u00a0forecast flashovers<\/a>\u00a0precious seconds before they erupt.<\/span><\/p>\n In 2015, scientists from King\u2019s College London and Sheffield Hallam University tested the possibilities of using r<\/span>obots equipped with tactile sensors to serve as\u00a0guide dogs for firefighters<\/a>\u00a0in smoked-filled interiors, enabling them to identify objects and obstacles.<\/p>\n