Operating an Automated Wild Fire/Forest Fire Detection System

Automated fire detection systems can only minimize wildfire damage if they have been configured correctly and are strategically operated.  Effective fire monitoring and suppression is more complex than merely watching a video screen and calling 911 when smoke appears.  While minimal expertise may be needed to confirm a forest fire, several expert judgments are necessary to communicate critical intelligence information to the responder teams.  Automated fire detection technology arms organizations with the potential for saving money, resources and lives, but there are steps they can still take to ensure they are getting the most out of their equipment's capabilities.

Effective fire suppression occurs with a combined effort of automated detection technology, system managers and rescue personnel.  Automated systems are designed to relieve fire lookout responsibilities so that human resources can be more efficiently allocated.  They assist fire management with quickly identifying fires and determining the best course of action. This technology is the first step to harnessing Mother Nature; how the fire operators and managers react determines the effectiveness of their fire suppression plan.

The following examples are based on the automated wildfire sensing system based on using visible light, standard security style video cameras for sensors and pattern recognition software as the detection and fire presence signaling system. As the examples show, this information is often integrated with field intelligence from other systems such as satellite mapping, meteorology reports, etc. Other approaches may vary in their application and operation from what is presented.

How the Automated System Detects Fire

The organization that installs the automated wildfire detection system cameras will typically set up an approximately 50-60° field of view by each sensor for detection.  The smaller the monitored area per sensor, the faster a wildfire can be detected.  This is true because most automated systems need a 10x10 pixel square of smoke to trigger an alert.  The area of land that is covered by the distance between pixels changes depending on how far zoomed out the field of view is. 

Installers can then set the cameras/sensors to move a specific number of degrees, and the camera continually sweeps the designated area, looking for signs of fire.  If the camera doesn't detect anything resembling smoke or fire, it moves on.  The cameras will continue surveying their designated areas; if one senses movement that looks like smoke, a yellow square, or some other alert will appear on the monitoring screen at the control center. 

The camera will continue to evaluate the highlighted area, going through all of its programming functions to determine whether the movement that was sensed is, in fact, a fire.  If the camera identifies the movement as a fire, the indicator light on the computer screen will change color to red within the alerted square and set off an audible alarm.  An audible alarm will alert an operator who may be away from the monitoring room.  The operator can then return to the control center and verify the fire.  After the fire is confirmed, the operator will then need to gather critical information in order to make the decisions that will result in a successful suppression.

How to Make Suppression Decisions

Once a fire is identified, either a fire operator or fire manager will need to gather important data to predict the escalation of danger and make suppression decisions.  Below is a list of methodological approaches personnel may wish to use to assess the current status of a fire and predict the path and rate of escalation.

  • Fire Location Assessment: Operators must pinpoint the exact location of the fire in order to understand where and how to allocate suppression resources.  A fire location assessment can be performed by using a locator function on an automated detection system.  An operator simply needs to move a cursor to the picture of the fire spot on the screen, and the system will reveal the exact latitude and longitude of that location.  The exact coordinates of a fire can then be sent to emergency personnel at a local control center or even to the cell phones or pagers of emergency responder managers so that they can target where to best use their resources.
  • Fuel Assessment: This includes both a fuel moisture content survey and an assessment of available fuels. Early warning systems can use meteorological danger indices and space-borne data on vegetation and soil dryness.  Automated fire detection software can also use satellite images to measure and estimate the amount of fuels available in a particular area.  This helps emergency personnel predict the strength of the fire (how fast it may spread).
  • Wildfire Path Assessment: Predicting the path of a fire includes studying the current path of destruction and identifying relevant weather data such as precipitation and wind speeds and directions. The operator or manager can then make a model or projection of where the fire is headed and where to send emergency personnel.
  • Smoke Pollution Prediction: Some systems can use satellite images to track smoke pollution based on surface wind predictions.  With this information, cities can issue alerts to nearby populations that may be affected.

Some organizations use automated fire detection technology in addition to environmental analyses to not only help organizations efficiently fight existing fires, but also help predict the potential for fires in a specific area.  For example, one prediction method includes studying the potential threat of human-caused fires in a particular area.  This requires the analysis of socioeconomic factors including housing ownerships, land uses, and unemployment rates, to name a few.  Some entities also predict the possibility of a lightning ignition.  This approach includes tracking lightning activity with ground-based lightning detection systems and space-borne monitoring systems.

The Manager and the Operator

Once an operational center receives a smoke alert from their automated detection software, the operator is the first person to use the computer-aided analysis to determine whether or not a fire actually exists.  False alarms may be triggered by a dust cloud from a combine harvester, for example, so human verification is important.  If a fire is confirmed, the operator will typically hand over the data to the manager who will gather additional information and coordinate further suppression operations with the local fire service.  Fire managers will often over take manual control of the cameras to continually watch the fire and communicate what resources are needed and where.  Image reporting helps offer all personnel a more comprehensive picture of the task at hand. 

Some centers may not have a fire manager available 24/7 and have to give their operators more responsibility for gathering data and making the initial suppression decisions.  Some organizations choose to staff their monitoring centers according to the different forest fire warning levels that are issued.  Although many automated fire detection systems offer user-friendly interfaces, it is still best that suppression operations are led by an experienced fire manager who not only knows how to use the software, but can also make quick decisions based on the aggregated data and confidently lead the fire dispatch teams.

Operational “Red Flags”

While not every fire management control center needs to operate in precisely the same manner, there a few operational concerns that may indicate a center is not using their technology in the most efficient or effective manner possible.  Some control centers use 911 dispatchers or other unskilled operators to run their fire detection software in order to reduce costs.  If an organization decides to make this personnel choice, it is imperative that the software is set up for easy access to all of the weather data and condition reporting necessary for fire suppression.  This includes, but is not limited to, environmental data, real-time weather data and any condition alerts. If an operator either does not have access to this data or does not know how to interpret the data, precious minutes are wasted until someone with this knowledge can arrive.  Similarly, if an organization has a highly-skilled fire manager on board who doesn't have access to an aggregated data center, the same inefficiency exists.

Additionally, if an operator is expected to make emergency dispatch decisions, he or she should know where all of the local emergency responders are located at any particular time.  Because successful suppression often means an integrated effort on the part of several different entities, it is not enough to call for help.  Whoever is leading the fire management team must be able to communicate how many people are needed and where.  In the early stages, the fire department is the only team that needs to be notified, but fire management leaders have a great responsibility to guide the initial suppression efforts. 

False Alarms: The “Interrupted” Operational Sequence

Another fire management issue occurs when an automated fire detection system sets off too many false alarms.  This may be a result of poor configuration or setup.  Nuisance alarms can occur as a result of cloud movement, cloud shadows on the ground, structure vibrations, camera vibrations and even the sun's reflection on bright surfaces.  Detection systems with continuous monitoring capabilities (rather than still image analysis) greatly reduce the number of false alarms since they can collect more data at a faster rate in order to analyze for a decision.  Some systems also have different sensitivity settings that may need to be adjusted for a reduction of nuisance alarms.  Overall, systems that are flexible and adjustable are most equipped at meeting an individual center's needs and reducing the frustration of false alarms.   

Operational best practice requires a skilled fire manager to lead the suppression efforts while using a host of critical data aggregated by an automated fire detection software program.  This approach is the most efficient and effective way to fight fires.  Organizations that invest in automated detection will only see the ROI they hope for if they both calibrate and use the technology correctly.  Automated fire detection technology is a powerful tool for saving money, saving resources and saving lives.