Life safety device with machine learning based analytics
A detector is provided. The detector includes a sensor configured to detect airborne particulates at a premises and processing circuitry. The processing circuitry is configured to determine a characteristic associated with the detected airborne particulates, compare the characteristic associated with the detected airborne particles to data associated with predefined characteristics of burned materials, detect, based at least on the comparison, presence of a fire; and determine, if the presence of the fire is detected, a characteristic of the fire based on the characteristic associated with the detected airborne particles and the comparison.
1. A detector, comprising:
at least one sensor configured to detect airborne particulates at a premises;
at least one processor in communication with the at least one sensor;
at least one memory storing instructions that, when executed by the at least one processor, cause the at least one processor to:
determine at least one characteristic associated with the airborne particulates, the at least one characteristic associated with the airborne particulates comprising a composition of the airborne particulates;
compare the at least one characteristic associated with the airborne particulates to data associated with predefined characteristics of reference particulates;
detect, based at least on a result of the comparison, a presence of an alarm condition; and
determine, in response to the presence of the alarm condition being detected, at least one characteristic of the alarm condition based at least on the at least one characteristic associated with the airborne particulates and the result of the comparison, the at least one characteristic of the alarm condition comprising an identity of a substance that is a source of the airborne particulates; and
indicate an egress point or an ingress point based on the at least one characteristic of the alarm condition.
2. The detector of claim 1 , wherein the at least one characteristic associated with the airborne particulates further comprises at least one of a spread pattern or a burn rate.
3. The detector of claim 1 , wherein the instructions are further configured to cause the at least one processor to determine, based on the at least one characteristic associated with the airborne particulates, a visibility condition at the premises.
4. The detector of claim 1 , wherein the airborne particulates correspond to a detected gas.
5. The detector of claim 4 , wherein the detected gas comprises at least one of carbon monoxide (CO), carbon dioxide (CO2), nitrogen dioxide (NCH), hydrochloric acid (HCL), nitrogen dioxide (NO2), or oxygen (O2).
6. The detector of claim 4 , wherein the at least one characteristic associated with the detected gas further comprises a burn rate of the detected gas.
7. The detector of claim 6 , wherein the at least one characteristic associated with the detected gas further comprises a gas level.
8. The detector of claim 7 , wherein the instructions are further configured to cause the at least one processor to transmit an alarm signal based at least on at least one of the burn rate of the detected gas or the gas level.
9. The detector of claim 1 , wherein the instructions are further configured to cause the at least one processor to obtain the data associated with the predefined characteristics of the reference particulates from a remote database.
10. The detector of claim 1 , wherein the sensor is further configured to detect at least one of volatile organic compounds or bacteria.
11. The detector of claim 1 , wherein the sensor is further configured to detect viruses.
12. The detector of claim 1 , wherein the airborne particulates are at least one of volatile organic compounds, bacteria, or viruses; and
the instructions are further configured to cause the at least one processor to request data specific to the at least one of volatile organic compounds, bacteria, or viruses from a database.
13. The detector of claim 1 , wherein the instructions are further configured to cause the at least one processor to apply a machine learning model to determine the at least one characteristic associated with the airborne particulates.
14. A method implemented by a detector, the detector comprising at least one sensor configured to detect airborne particulates at a premises, the method comprising:
determining at least one characteristic associated with the airborne particulates, the at least one characteristic associated with the airborne particulates comprising a composition of the airborne particulates;
comparing the at least one characteristic associated with the airborne particulates to data associated with predefined characteristics of reference particulates;
detecting, based at least on a result of the comparison, a presence of an alarm condition; and
determining, in response to the presence of the alarm condition being detected, at least one characteristic of the alarm condition based at least on the at least one characteristic associated with the airborne particulates and the result of the comparison, the at least one characteristic of the alarm condition comprising an identity of a substance that is a source of the airborne particulates; and
indicating an egress point or an ingress point based on the at least one characteristic of the alarm condition.
15. The method of claim 14 , where the at least one characteristic associated with the airborne particulates further comprises at least one of a spread pattern or a burn rate.
16. The method of claim 14 , further comprising determining, based on the at least one characteristic associated with the airborne particulates, a visibility condition at the premises.
17. The method of claim 14 , wherein the airborne particulates correspond to a detected gas; and
the at least one characteristic associated with the detected gas further comprises at least one of a burn rate of the detected gas or a gas level.
18. The method of claim 17 , further comprising transmitting an alarm signal based at least on at least one of the burn rate of the detected gas or the gas level.
19. The method of claim 14 , wherein the sensor is further configured to detect at least one of volatile organic compounds or bacteria.
20. The method of claim 17 , wherein the airborne particulates are at least one of volatile organic compounds, bacteria, or viruses; and
the method further comprising requesting data specific to the at least one of volatile organic compounds, bacteria, or viruses from a database.