With temperatures and abnormal weather patterns on the rise thanks to climate change, fighting wildfires is getting harder and more devastating. Last year, fires in Australia ravaged the continent, wiping out 27 million acres of land. Fires in the mainland U.S. tore through 2.2 million acres nationwide. This year, California has already reported an increase in fires and below average snow and rainfall patterns.
While environmental conditions have worsened, the number of technologies designed to help fight fires has grown: Drones and IoT sensors now help with fire detection, and departments can choose from better, more protective equipment options for their firefighters.
But despite these strides, most fire departments are still not ready for today’s fires because their operations are not data-driven. Without the ability to study their operational data, departments cannot learn from their mistakes or edit best practices based on their successes. Everything from containment strategies to staffing is left up to chance.
And with the evolving global environment still ongoing, fighting wildfires this summer will be even harder. Due to enforced social distancing and the shelter-in-place orders of some states, typical staffing and training programs have changed — some were even cancelled. Now more than ever, as fire departments face steeper challenges, longer battles and the current health crisis, they need data-driven technologies that strengthen their ability to forecast and combat wildfires now and into the future.
Leveraging Technology to Train in Challenging Times
More wildfires in 2020 are imminent, but during our current public health situation, firefighters worry that they won’t be able to do their jobs without putting themselves at greater risk. As a population, firefighters are more susceptible to contracting infectious diseases: They work long hours in close proximity to one another in less than sanitary conditions. And firefighting crews have been hit by epidemics before: In 2009, there was a norovirus outbreak in firefighter encampments following Nevada’s Red Rock Fire that infected both firefighters and evacuees.
Nonetheless, the need for trained firefighters remains. And to make matters worse, training to become an active duty firefighter is no small feat: Individuals have to spend up to 600 hours in training. To become a wildland firefighter — the kind that puts out wildfires and prevents future ones from starting — training is even more extensive and can take anywhere between three months to a year to complete.
Typically, fire departments train new recruits in a classroom-setting before moving them into the field of service — a kind of in-person learning that’s no longer an option due to the pandemic. Washington state canceled all nonessential training, while one southern California fire department halted routine preparations for the upcoming fire season. To maintain training despite social distancing, some departments have turned to digital learning — with data at its core.
For example, one department based outside of Los Angeles, CA had already replaced its paper-based training curriculum with digital learning tools and technologies so that its firefighters can learn wherever and whenever. From iPads that are preloaded with the necessary courses, firefighters can be remotely trained on everything from how to handle hazardous materials to getting ready for fire season.
Then, using a digital tracking system, the department collects data on its firefighters’ training records and certifications to determine which firefighters are ready for wildfire season and which are not — and if needed, take action to fill the gaps.
Leveraging Data-Driven Technologies for Better Firefighting
Beyond remote training and development tracking, there are numerous data-driven technologies available to help departments upgrade the effectiveness of their operations. For example, across the western U.S., fire departments have adopted data modeling, a technology that replicates any environment or object so that it can be studied and tested against different variables. For fire departments, data models are typically used to help crews gain a better understanding of where and when a fire will start.
Data scientists collect information, like the amount of combustible materials and flammable waste, potential heat sources, weather conditions and historical information of an area. And, based on this data, they can create models to take appropriate preventative actions against imminent fires.
A handful of fire departments have taken a step further, adopting a cyber-infrastructure system that uses data modeling to track and predict the spread of wildfires once they start. The platform uses artificial intelligence to examine and analyze high-resolution satellite imagery. The system will look for potential fuel sources like large patches of dry and flammable brush, for example, and will flag them if present in areas vulnerable to wildfires. During a wildfire, fire departments can use the system to forecast how the fire will move and its rate of acceleration.
Fighting Fires with Digital Twins
As we look into the future of firefighting, and as environments and climate patterns become more dynamic, departments will need data on more than just the current state of an environment — they will need technologies that track the evolution of an environment, like digital twinning.
Similar to data modeling, digital twins can help forecast the path of a fire by collecting information on an environment. They mimic existing objects or areas — but unlike typical data models, which typically provide a snapshot of an environment’s behavior at a specific moment, a digital twin is an online replica that’s updated or adjusted based on how data of the environment changes over time.
To create a digital twin, additional technologies like IoT sensors and drones are used to collect real-time data on an environment. These devices reveal many aspects of an environment, including factors like weather, wildlife, supply chain and maintenance. Machine learning, AI and other advanced modeling techniques are then applied to this information to create a precise digital duplicate that mimics how an environment reacts to changes over time. Therefore, with digital twinning technology, fire departments can simulate fires and develop effective containment strategies given every environmental or situational change.
“With this predictive, machine learning technology, fire departments can minimize the impact of wildfires and evacuate citizens more quickly and as needed,” explains Suraj Rao, Senior Director, Data Science, and Head of the Digital Analytics Office at Western Digital.
Previously, most fire departments lacked the ability to leverage their own data. But this global health situation has been a stark reminder of this technology gap, especially as global temperatures and climate patterns also become more extreme. With data, fire departments can adapt their operations to defeat wildfires, save lives and protect ecosystems, even in worsening conditions.
This content is produced by WIRED Brand Lab in collaboration with Western Digital Corporation.
- fighting wildfires is getting harder and more devastating
- 27 million acres
- 2.2 million acres nationwide
- an increase
- technologies designed to help fight fires have grown
- most fire departments are still not ready for today’s fires
- firefighters are more susceptible to contracting COVID-19
- a norovirus outbreak in firefighters
- Individuals have to spend up to 600 hours
- canceled the first of three firefighter training
- one southern California fire department halted routine
- replaced its paper-based training curriculum with digital learning tools and technologies
- A digital tracking system
- cyber-infrastructure system
- digital twins
- additional technologies
- precise digital duplicate