The advancements in technology have resulted in the increased connectivity of devices and even whole building systems. This means the Internet of Things (IoT) is an additional tool for fire investigations.
Over the last 10 years, modern construction has increased the use of integrated IoT building management systems, which include smoke alarms, fire suppression systems, heating, and cooling systems (HVAC), access control systems, and even automated machines. When each of these systems is part of an IoT ecosystem, fire investigators have additional data points to assist in making origin and cause determinations.
Smoke alarms are the most obvious and simplest sources of data to narrow origin, but how would other devices assist? A great example is a fire that occurred at a nail salon equipped with a digital electrical meter and IoT-enabled HVAC system. The electrical meter tracks power usage down to the minute, allowing investigators to determine the exact minute the fire began imping on branch circuits and which direction the fire spread, based upon usage declines associated with equipment draw loads cessations.
Knowing that before the fire, the typical draw was 100 kilowatts per hour (kWh) an hour. But an hour before the fire department arrived, the draw dropped to 95 kWh, or the amount the dehumidifier draws, telling us when there was fire impingement on the dehumidifier. If the dehumidifier is in the suspected area of origin, then the origin point can be determined with greater accuracy.
Alternatively, if the meter shows 0 kWh draw 40 minutes before the arrival of the fire department, then an investigator can approximate when the fire burned through the drywall and began to impinge on the branch circuits. Competent investigators can approximate an ignition time and support area of origin determinations by working backward (i.e., two-hour fire rating drywall), the distance of impingement from the potential area of origin and available fuel packages.
Another real world example is a fire that occurred at an unoccupied warehouse. The warehouse was equipped with a monitored burglar alarm and interior video system. Using sketches of the video camera, electrical circuitry and ethernet locations, investigators could use the signal loss notifications from each of the cameras and burglar alarm activations to develop a timeline of events and overlay those data points onto a map of the structure. As a result, investigators were able to narrow down the area of origin to a 20-square-foot area of the total 104,000 square feet burned.
With the inclusion of internet connectivity in more devices and building systems, leveraging them for the origin and cause investigations is approaching near universality. While the presence of data is helpful, the sabotage or disruption of that IoT is relevant to supporting hypotheses of human factors as causes. Not only is IoT data, or the absence of that data, unbiased and truly reliable, it is superior to witness statements and fire pattern analysis. Because fire pattern interpretation and witness statements can be the basis for alternative hypotheses by competing experts, IoT data shut the door on “creative” interpretations. IoT data is a powerful tool in the modern fire investigation arsenal, only increasing in usefulness as technology advances.
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