{"id":58024,"date":"2018-11-22T00:00:00","date_gmt":"2018-11-21T22:00:00","guid":{"rendered":"https:\/\/richardvanhooijdonk.com\/blog\/can-we-fight-wildfires-with-artificial-intelligence-machine-learning-and-big-data\/"},"modified":"2021-07-12T13:02:24","modified_gmt":"2021-07-12T11:02:24","slug":"can-we-fight-wildfires-with-artificial-intelligence-machine-learning-and-big-data","status":"publish","type":"post","link":"https:\/\/blog.richardvanhooijdonk.com\/en\/can-we-fight-wildfires-with-artificial-intelligence-machine-learning-and-big-data\/","title":{"rendered":"Can we fight wildfires with artificial intelligence, machine learning, and big data?"},"content":{"rendered":"<ul class=\"bold-list\">\n<li>Wildfires are increasing in frequency and intensity<\/li>\n<li>WIFIRE uses big data to predict and fight wildfires<\/li>\n<li>Artificial intelligence could also help predict wildfires before they start<\/li>\n<\/ul>\n<p>The tremendous impact climate change has on our planet is becoming more and more pronounced and terrifying with each passing day. Natural disasters like earthquakes, floods, and hurricanes &#8211; which used to occur with much less frequency &#8211; are becoming an increasingly common occurrence, with the next one always seeming to be lurking right around the corner.<\/p>\n<p><iframe title=\"Can we fight wildfires with artificial intelligence, machine learning, and big data?\" width=\"800\" height=\"450\" src=\"https:\/\/www.youtube.com\/embed\/8PSfLfAYqng?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>One of the most devastating and deadliest consequences of <a href=\"https:\/\/blog.richardvanhooijdonk.com\/en\/blog\/can-carbon-capture-technology-help-us-reverse-the-effects-of-climate-change\/\">climate change<\/a> has been the increase in the frequency and intensity of wildfires, particularly in the North American region. And with global temperatures expected to keep rising, finding a more effective way to deal with this growing problem as soon as possible is becoming increasingly critical. Some researchers believe that technologies like artificial intelligence, machine learning, and <a href=\"https:\/\/blog.richardvanhooijdonk.com\/en\/blog\/big-data-trends\/\">big data<\/a> could be the solution we\u2019re looking for.<\/p>\n<h2>Wildfires are increasing in frequency and intensity<\/h2>\n<p>Over the past decade, wildfires have caused more than $5 billion worth of damages in the United States. <a href=\"https:\/\/www.nifc.gov\/fireInfo\/nfn.htm\">According to<\/a> the National Interagency Fire Center, more than 52,000 wildfires have been recorded in 2018 so far, burning more than 3.4 million square kilometres of land and destroying thousands of homes in the process. The Campfire alone, which broke out in California\u2019s Butte County on November 8, 2018, has already destroyed more than 11,000 homes and killed 77 civilians, making it the deadliest and most destructive wildfire in the history of the state. The vast majority of wildfires, around 90 per cent of them, are caused by people, while the remaining 10 per cent are caused by naturally occurring phenomena, such as lightning. Wildfires can spread incredibly quickly, <a href=\"https:\/\/www.nationalgeographic.com\/environment\/natural-disasters\/wildfires\/\">reaching<\/a> speeds of up to 23 kilometres per hour and devouring everything that gets in their way. The one thing that makes wildfires particularly dangerous is that they\u2019re highly unpredictable. They can change direction in a matter of seconds, forcing firefighters to have to constantly adapt to changing conditions on the ground. And this is precisely where artificial intelligence, machine learning, and big data can lend a helping hand.<\/p>\n<figure id=\"attachment_35357\" aria-describedby=\"caption-attachment-35357\" style=\"width: 800px\" class=\"wp-caption aligncenter\"><img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-35357 size-full\" src=\"https:\/\/blog.richardvanhooijdonk.com\/wp-content\/uploads\/sites\/4\/2019\/05\/wildfireee.jpg\" alt=\"Three firefighters trying to control forest fire\" width=\"800\" height=\"526\"><figcaption id=\"caption-attachment-35357\" class=\"wp-caption-text\">Over the past decade, wildfires have caused more than $5 billion worth of damages in the United States.<\/figcaption><\/figure>\n<h2>WIFIRE uses big data to predict and fight wildfires<\/h2>\n<p>WIFIRE is an integrated fire analysis web platform that uses signal processing, data assimilation, modelling, and visualisation techniques. These technologies are used to combine satellite imagery with with real-time data supplied by cameras and sensors to create a dynamic map of the fire, including the conditions around it and its most likely trajectory. The system incorporates a wide variety of factors to predict how the fire will develop, including current and historical weather data, wind conditions, topography, roads, and past fires. The data is fed into machine learning software, where it\u2019s analysed and then displayed on the map, which is updated every 15 minutes.<\/p>\n<p><iframe title=\"WIFIRE helps firefighters get a jump on wildfires - Science Nation\" width=\"800\" height=\"450\" src=\"https:\/\/www.youtube.com\/embed\/N4LAROiW5c8?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture\" allowfullscreen><\/iframe><\/p>\n<p>The data is obtained from various sources, including US Forest Service sensors, San Diego Gas &amp; Electric weather stations, weather data from the National Weather Service, and the HPWren project by the University of California San Diego. \u201cWe are using various analytical, machine learning, Geographic Information Systems (mapping) and signal processing techniques to curate and visualize the data sets,\u201d <a href=\"https:\/\/www.delltechnologies.com\/en-us\/perspectives\/how-big-data-is-helping-predict-and-fight-wildfires\/\">explains<\/a> Ilkay Altintas, WIFIRE\u2019s principal investigator. \u201cWe have developed techniques to compare the models over time to the data we are receiving from the fire and we can dynamically adjust the model as we receive information. That\u2019s the real innovation here: dynamic adjustments over time.\u201d<\/p>\n<p>In fact, WIFIRE has proven so accurate in its predictions that it\u2019s already gained the trust of the Los Angeles Fire Department and is now regularly used in their firefighting efforts. \u201cWhat the tool gives us is within the initial action phase, really within minutes, we\u2019re able to run a model of the incident and have a computer model of where this fire is predicted to spread,\u201d <a href=\"https:\/\/www.delltechnologies.com\/en-us\/perspectives\/how-big-data-is-helping-predict-and-fight-wildfires\/\">says<\/a> the LAFD Commander Carlos Calvillo. \u201cFor the initial action commanders who are trying to make decisions, when they\u2019re going off their experience, they\u2019re going off their gut, this can confirm or reconfirm how they thought the fire was going to spread or give them indications of where it will go that they haven\u2019t even thought of.\u201d<\/p>\n<h2>Artificial intelligence could also help predict wildfires before they start<\/h2>\n<p>But what if, instead of focusing our efforts on fighting wildfires after the fact, there was a way to predict where they\u2019re most likely to break out and take preventative measures? Researchers from the University of Alberta and the University of Oklahoma have developed a computer program that uses AI to analyse raw meteorological data associated with past wildfires and identify locations with conditions suitable for the next wildfire outbreak. <a href=\"https:\/\/www.cbc.ca\/news\/canada\/edmonton\/artificial-intelligence-alberta-wildfire-1.4239137\">Described<\/a> by the researchers as a \u2018self-organising map\u2019 (SOM), the program uses an artificial neural network modelled after the human brain to look for meaningful patterns in the data it\u2019s fed and make predictions about future events.<\/p>\n<p>\u201cThere are a lot of fires on the landscape, but you need three ingredients for fire. You need the fuel; the trees, the shrubs, the grass. You need the ignition \u2014 people and lightning \u2014 and you need conducive weather, hot, dry windy weather,\u201d <a href=\"https:\/\/www.cbc.ca\/news\/canada\/edmonton\/artificial-intelligence-alberta-wildfire-1.4239137\">explains<\/a> Mike Flannigan, a co-author of the study and professor at the University of Alberta&#8217;s department of renewable resources. \u201cIf we can get a better handle on those extremes, then we can be better prepared \u2026 We can look ahead for the next where and when.\u201d While a similar approach has been used in the past to predict monsoons and other extreme weather events, it\u2019s never been applied to wildfires \u2014 until now.<\/p>\n<p>With wildfires increasing in frequency and intensity in recent years due to climate change, it\u2019s become clear that our existing fire management and prevention methods are no longer enough to protect us. Thankfully, technology offers a solution. Systems that use artificial intelligence, machine learning, and big data could help us better predict the spread of wildfires and anticipate where they\u2019re most likely to break out, allowing us to react before they even start. These automated tools enable firefighters to analyse conditions on the ground in real time and help them make critical decisions that will save people\u2019s lives and protect their homes from destruction.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Wildfires are increasing in frequency and intensity WIFIRE uses big data to predict and fight wildfires Artificial intelligence could also help predict wildfires before they start The tremendous impact climate change has on our planet is becoming more and more pronounced and terrifying with each passing day. Natural disasters like earthquakes, floods, and hurricanes &#8211; [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":50709,"parent":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","footnotes":""},"categories":[2860],"tags":[4218,4468,4573,4470],"article-type":[],"trends":[5485],"class_list":["post-58024","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-agriculture","tag-future","tag-machinelearning","tag-tech-en-2","tag-wildfire","trends-artificial-intelligence-en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Can we fight wildfires with artificial intelligence, machine learning, and big data? - Richard van Hooijdonk Blog<\/title>\n<meta name=\"description\" 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