During operation, the AI system receives information from three types of detectors/sensors: fire propagation sensors, structure health sensors and population sensors.
Fire Propagation Sensors Smart fire detectors such as gas analysers, smoke, CO, temperature and IR sensors are connected to a common network. As fire progresses through its phases (ignition, smoldering, growth and propagation), fire detectors are triggered at respective phases depending on their proximity to the ignition source. Input data to the AI system are spatial and temporal distribution of different fire related measurements. Thus, the trained AI system can identify location of the fire, what is burning, rate of fire growth and direction(s) of fire propagation.
Population sensors: Approaches to record movement of occupants in and around a building include technologies such as CCTV, footpads, passive or active detectors, WIFI/Bluetooth/GPS counts and dedicated people sensors (infrared, beam, LIDAR, etc.). Given the connectivity of population sensors to a common network, spatial and temporal distribution of occupants are available to the AI system. In addition to the spatial and temporal distribution of fire related measurements, the trained AI system returns optimal evacuation paths for individual occupants.
Structural Health Sensors Structural health sensors such as thermocouples, strain gauges and fibre optics are used to gather information regarding thermal and structural load conditions. Data gathered are the main input to the structure health AI component which predicts information on the structural integrity and conveys it to first responders.