Fighting Fire with Technology
By Jayden Kyryluk, 2026 JD Candidate, University of Manitoba, Faculty of Law
With our once blue skies now hued with smoke grey, one need only look up to grasp the reality of wildfires. In 2025 alone, 1,744,778.7 hectares have burned in Manitoba, a leap from 52,485 in 2024.[1] Nationally, the toll is even greater: 7,403,657hectares burned in 2025, up from 1,810,800 the year before and now the second worst on record behind 2023.[2] Thousands have been displaced across the country, and while traditional firefighting methods, such as ground crews, helicopters, and water bombing, remain necessary, a new force is emerging from the haze.
Enter technology and artificial intelligence (“AI”): Can machine learning, drones, cameras, datasets, and satellites form the next line of defence against wildfires? This blog explores three emerging technologies in firetech poised to help the fight against wildfires.
1. Predicting Wildfires Before They Ignite
While wildfires have always been unpredictable by nature, innovations in AI are beginning to change that. LSU’s DeepFire system, for instance, claims 90% wildfire prediction compared to about 70% for traditional methods.[3] This higher accuracy allows jurisdictions to take pre-emptive action and mitigate fire damage before it occurs. DeepFire draws on extensive datasets, such as past wildfire records, real-time weather, lightning forecasts, land cover, and vegetation types, to assess fire risk days or even weeks in advance.[4] By integrating prediction, detection, and spread-modelling systems, it pinpoints high-risk zones and guides the strategic deployment of resources.[5]
Applied in Canada, such technology could help provinces like Manitoba strengthen early warning systems, prioritize high-risk regions such as the heavily forested North, and deploy firefighting resources more efficiently. Integrated with tools like the Canadian Wildland Fire Information System, which creates daily fire weather and fire behavior maps year-round, AI forecasting could improve real-time decision-making and help fight the growth of wildfires.
2. Early Detection: Satellites, Cameras & Sensors
It goes without saying that time is critical in wildfire response. Recognizing this, companies and public agencies have begun utilizing a combination of emerging technologies such as satellites, cameras & sensors to shorten detection times. Google’s FireSat project uses a constellation of satellites dedicated to wildfire monitoring, providing near real-time detection with high-resolution multispectral imagery updated every 20 minutes.[6] The satellites are able to detect fires 1/400th the size that early detection satellites could, or approximately 5×5 meters or the size of a classroom.[7] Moreover, ALERTCalifornia, a public safety program, deploys 1,100 tower-mounted pan-tilt-zoom cameras across California to detect wildfires.[8] AI then lifts the burden of needing a human operator to observe every camera, saving precious manpower.
Knowing where a fire will go next is also important. USC researchers recently developed a generative AI model that tracks a wildfire’s evolution using satellite imagery to accurately predict progression, direction, and intensity.[9]
In Canada, startups and agencies are building on that framework: SenseNet combines AI with ground sensors, cameras, and satellite feeds to detect fires in real time and support immediate action.[10] Like FireSat, the Canadian Space Agency’s Mission Control project is developing AI algorithms that run directly onboard satellites to detect wildfires in near real-time, in turn enabling faster and more coordinated responses.[11]
3. Unmanned Aerial Systems
Unmanned aerial systems (“UAS”), otherwise known as drones, are becoming powerful tools in the fight against wildfires. They offer quick deployment and can detect, monitor, and even suppress fires faster and more safely than traditional methods.[12] Unlike manned aircraft, drones reduce the risks faced by pilots; between 2006 and 2016, plane and helicopter crashes accounted for 24% of all firefighting-related deaths in the United States.[13]
In Canada, FireSwarm Solutions, based in BC, is pioneering AI‑controlled drone swarms capable of dropping retardant or water up to 880 lbs each.[14] These drones help fill a wildfire prevention gap by flying safely at night, in low visibility, and in conditions unsafe for pilots.[15]
Rain, a California-based company, develops autonomous wildfire suppression technology that pairs mission-autonomy software with Black Hawk helicopters for rapid fire detection and response.[16] In partnership with Sikorsky, a Lockheed Martin subsidiary, Rain integrates two advanced systems: Sikorsky’s MATRIX technology, which enables autonomous flight for both crewed and uncrewed aircraft, and Rain’s wildfire mission software, which identifies and tracks fires, formulates suppression plans, and guides the aircraft to perform targeted water drops.[17]
These innovations in both Canada and the United States position unmanned aerial systems as a safer, faster, and more adaptable tool in the fight against wildfires than manned alternatives.
Conclusion
As Canada faces more and more severe wildfire seasons, technology and AI offer faster, safer, and more strategic tools for response. From predictive modelling that warns days in advance, to real-time detection from space and to autonomous aerial systems capable of operating in the most dangerous conditions, these innovations can complement traditional firefighting methods. As the haze of smoke continues to cloud the skies of Canada, it is clear that any and all help against wildfires is needed. By integrating such tools into national and provincial wildfire strategies, Canada can better protect its people and natural beauty from uncontained wildfires.
[1] Canadian Interagency Forest Fire Centre Inc, “Current Fires Summary” (12 August 2025) online: <https://ciffc.net/summary>.
[2] Ibid.
[3] https://www.lsu.edu/winning-teams/2024-25/wildfire-detection.php
Louisiana State University, “Wildfire Detection and Prediction Made Better Through AI” online: <https://www.lsu.edu/winning-teams/2024-25/wildfire-detection.php>.
[4] Ibid.
[5] Ibid.
[6] Google Research, “FireSat” online: <https://sites.research.google/gr/wildfires/firesat/>.
[7] Ibid.
[8] American Society of Civil Engineers, “Artificial intelligence detects fires early, protecting people and infrastructure” (14 November 2024) online: < https://www.asce.org/publications-and-news/civil-engineering-source/article/2024/11/14/artificial-intelligence-detects-fires-early-protecting-people-infrastructure> [
[9] Nina Raffio, “USC scientists use AI to predict a wildfire’s next move” (22 July 2024) online: <https://today.usc.edu/using-ai-to-predict-wildfires/>.
[10] SenseNet, “Early Wildfire Detection When Every Second Counts” online: <https://www.sensenet.ca/>.
[11] Government of Canada, “From satellite data to environmental solutions: five Canadian projects” (3 July 2025) online: <https://www.asc-csa.gc.ca/eng/news/articles/2025/2025-07-03-satellite-data-environmental-solutions-five-canadian-projects.asp>
[12] Thomas Frey, “Using Drones to Eliminate Future Forest Fires” (22 August 2018), online: <https://futuristspeaker.com/technology-trends/using-drones-to-eliminate-future-forest-fires/>
[13] Ibid.
[14] FireSwarm Solutions, “Ultra Heavy-Lift Automated Aeriel Fire Suppression” online: <https://www.fireswarmsolutions.com/>.
[15] Ibid.
[16] Lockheed Martin, “Rain and Sikorsky Test Advanced Aerial Firefighting Technologies Using Autonomous Black Hawk® Helicopter” (1 May 2025) online: < https://news.lockheedmartin.com/2025-05-01-Rain-and-Sikorsky-Test-Advanced-Aerial-Firefighting-Technologies-Using-Autonomous-Black-Hawk-Helicopter>.
[17] Ibid.
The views and opinions expressed in the blogs and case reporter are the views of their authors, and do not represent the views of the Desautels Centre for Private Enterprise and the Law, the Faculty of Law, or the University of Manitoba. Academic Members of the University of Manitoba are entitled to academic freedom in the context of a respectful working and learning environment.