How big data is changing the ways we fight fires

Big data may also be able to help fire departments use their resources more efficiently and ensure they are prepared when they get called out to an incident

16Apr

Big data is changing nearly every industry, so it is not surprising that it has begun to play a role in fighting fires. Here is how fire departments and other groups are using big data to help prevent, prepare for and put out flames.

Using analytics to estimate fire risk

One of the main ways we can use big data to fight fires is by using analytics to predict where they are most likely to occur. Officials can use this information to decide which buildings to inspect first.

In Atlanta, for example, the fire department worked with analysts from Data Science for Social Good to find commercial buildings that were missing from its inspection list. They then used an algorithm to determine which attributes of a structure were the best predictors of fire risk.

New Orleans has also used data to determine which homes to distribute free smoke detectors to. Data scientists developed a tool that could predict which city blocks had the highest fire risk and were the most likely not to have smoke detectors. The device, called Smoke Signals, is now also available to other cities.

New York City has become perhaps the most famous example of using big data to help prevent fires. The city's fire department maintains a database that includes 60 factors related to buildings' fire risk. An algorithm called FireCast ranks the structures according to fire risk, which helps determine which ones get inspected first. The tool helps ensure that the most at-risk buildings get inspected and eases the fire department's workload.

Some factors that such a system might consider are the age of the buildings, how it is used and the results of fire and flammability testing. For example, the New York City Fire Department found that older buildings, those with active tax liens and those with ongoing foreclosure proceedings are at a higher risk.

Predicting the path of wildfires

Big data can similarly be used to help fight wildfires. The Los Angeles Fire Department uses a tool called WIFIRE to predict where wildfires will go next. The web-based platform uses signal processing, data assimilation, modeling and visualization to merge satellite imagery, footage from cameras and data from sensors to create a picture of a fire and the conditions that surround it. It can then use current and historical data to predict what will happen next.

During the Thomas Fire in California in 2017, the system updated its information every 15 minutes. Firefighting teams used the system to monitor the fire and prepare for what it may do next. The public also used the app to stay up to date and determine whether they may need to evacuate.

Keeping equipment maintained

Big data may also be able to help fire departments use their resources more efficiently and ensure they are prepared when they get called out to an incident. Sensors affixed to fire engines can keep track of how much water is being used, how much diesel is left and how far trucks are driven. The City of Amsterdam Fire Department is an example of a department that uses smart fire engines.

The Internet of Things (IoT) enables predictive maintenance through sensors that monitor equipment performance and pick up signs that repairs are required. Plant managers often use this technology for industrial machinery. Fire departments could also use it to keep their equipment in good condition so they are prepared for incidents when they occur.

Improving response times

One of the ongoing challenges for fire departments is how to improve response times. Reducing the time it takes to get to the scene of a fire, even by a small amount, can make a significant difference. Big data could help fire departments determine what impacts how long it takes fire engines to arrive so they can improve their response times.

By collecting data surrounding response times and comparing it to the times themselves, scientists may be able to uncover patterns. Traffic, population density, street conditions and time of day could all be influential factors. Data analysis may provide evidence that streets with lots of potholes, for example, lead to slower response times. This evidence may convince local leaders to prioritize fixing the conditions of roads, especially in fire-prone areas.

Additionally, data analysis can help determine the fastest route to a scene. Big data already drives apps like Google Maps, which can show the fastest possible way in real time. Fire departments may be able to create similar technology that is specific to their needs.

The 'Firebrary'

Sharing data between fire departments could make information much more useful and provide benefits around the world. To do this, departments need a common language to describe the data they collect. That is the idea behind Firebrary, a glossary of firefighting terms and definitions created by firefighters in the Netherlands.

Establishing this common language enables departments to analyze data on a larger scale and share insights with other groups. It could help lay the foundations for further analysis and innovations.

Big data is changing nearly every sector, including firefighting. Fire departments can use data analytics to estimate risk, track the movement of wildfires, monitor equipment condition, improve response times and more. Ultimately, big data can help to prevent fires and put them out faster.

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