For a firefighter, anticipating sudden temperature change is difficult. Modern PPE materials offer greater protection, reducing the individual’s ability to connect with their environment. This is particularly difficult for trainees, who have yet to develop the intuition derived from experience.

FiRST is a simple and robust wearable technology that employs artificial intelligence to accurately predict increases in temperature, giving the firefighter more time to decide on the best course of action.
Following the successful completion of the initial test and evaluation phase, at two fire training establishments in the UK and US, we are now looking for a number of additional training centres to act as Evaluation Partners to help us perfect the technology.

Providing advanced warning of sudden temperature increases

By analysing the changes in ambient temperature and comparing it to data from previous fires, FiRST is able to provide between 15 and 30 seconds warning of sudden temperature increases.

System features

Enclosed antenna to send data to command post (future planned enhancement).
Robust thermocouple – exposed position to ensure responsive and accurate temperature measurement.
Unit Status LED (on / off / replace battery)
Precautionary (150°C) and Full (300°C) alarm indicators using bright blue LEDs to help in low visibility
Simple key-based activation (unit activates on key removal)
Loud audible feedback for both alarm states (>100dB)
Temperature and water resistant housing
Long battery life (80hrs normal operation)
Data logging, downloadable via USB port
Lightweight: <300g

How it works

Through its advanced machine-learning algorithms, FiRST has been ‘taught’ to predict increases in temperature from data derived from live firefighting in the UK and US, including residential fire experiments undertaken by the US National Institute of Science and Technology.

The ambient temperature surrounding the firefighter is measured every three seconds using a thermocouple at shoulder level. By looking at the last ten measurements, the unit can estimate what the next ten measurements are likely to be. It then uses a mathematical algorithm to determine the likelihood of the temperature exceeding the two pre-defined alarm states, which have been selected based upon feedback from real firefighters during testing.

In addition to providing real-time decision support to the firefighter, the data is also logged on the device, allowing post-event analysis and further refinement of the FiRST algorithm.

Future planned enhancements include adding the ability to transmit measured ambient and predicted temperatures back to the incident command post via low-bandwidth RF telemetry or via Bluetooth integration into the firefighters existing equipment.

Our Evaluation Partners

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Find out more

Interested in getting involved? If you would like to find our more about FiRST, either as a user or as a system integrator, call us on + 2392 584 222 or send us a message.