Method and system for fire detection

1. A hazard detection system, the system comprising:

a plurality of sensors configured to measure attributes associated with a hazard and generate sensor readings; and

a detection device configured to determine whether the hazard exists or not based on a fuzzy analysis of the sensor readings, wherein:

the sensor readings include temperature readings: and

the fuzzy analysis comprises:

determining a temperature rise rate from the temperature readings;

classifying the temperature rise rate by assigning a classification value in the range 0 to 1;

categorizing the temperature rise rate and the temperature readings into respective fuzzy set categories; and

combining the respective fuzzy set categories into an output that indicates whether the hazardous condition exists or not.

2. The system of claim 1 , wherein:

the attributes include one or more of temperature values, temperature rise rates, smoke concentrations and carbon monoxide (CO) concentrations; and

the plurality of sensors include one or more of temperature sensors, smoke sensors, CO sensors and infrared sensors.

3. The system of claim 2 , wherein:

the smoke sensor is an ionization smoke sensor configured to measure percentage obscuration due to smoke.

4. The system of claim 2 , wherein:

the carbon monoxide (CO) sensor is a tin oxide element based sensor configured to measure CO concentration.

5. The system of claim 1 , wherein:

the detection device comprises a fuzzy inference module configured to:

assign fuzzy set categories to the sensor readings; and

combine the fuzzy set categories into an output indicating whether the hazard exists or not.

6. The system of claim 1 , wherein:

the detection device comprises a classifier module configured to assign classification values to the sensor readings using a neural network, wherein the classification values lie in a range of 0 to 1.

7. The system of claim 6 , wherein:

the detection device further comprises a fuzzy inference module configured to:

assign fuzzy set categories to the sensor readings and the classification values; and

combine the fuzzy set categories into an output indicating whether the hazard exists or not.

8. The system of claim 1 , wherein:

the detection device is further configured to raise an alarm if the hazard exists.

9. The system of claim 1 , wherein:

the hazard is either a fire or a gas leak.

10. A method for detecting a hazardous condition, the method comprising:

receiving sensor readings from a plurality of sensors for attributes related to the hazardous condition; and

determining whether the hazardous condition exists based on a fuzzy analysis of the sensor readings, wherein:

the sensor readings include temperature readings: and

the fuzzy analysis comprises:

determining a temperature rise rate from the temperature readings;

classifying the temperature rise rate by assigning a classification value in the range 0 to 1;

categorizing the temperature rise rate and the temperature readings into respective fuzzy set categories; and

combining the respective fuzzy set categories into an output that indicates whether the hazardous condition exists or not.

11. The method of claim 10 , wherein:

the plurality of sensors includes one or more of temperature sensors, smoke sensors, carbon monoxide sensors and infrared sensors.

12. The method of claim 10 , wherein:

the sensor readings include one or more of temperature readings, percentage smoke obscuration readings and carbon monoxide (CO) concentration values.

13. The method of claim 10 , wherein the fuzzy analysis comprises:

categorizing the sensor readings into fuzzy set categories; and

combining the fuzzy set categories into an output that indicates whether the hazardous condition exists or not.

14. The method of claim 10 , wherein:

the hazardous condition is either a fire or a gas leak.

15. A device for detecting a fire, the device comprising:

a fuzzy inference module configured to receive classification values and sensor readings corresponding to a plurality of sensors that measure one or more fire related attributes, to categorize the classification values and the sensor readings into fuzzy set categories, and, wherein:

the sensor readings include temperature readings; and

wherein, the fuzzy inference module is configured to:

determine a temperature rise rate from the temperature readings;

classify the temperature rise rate by assigning a classification value in the range 0 to 1;

categorize the temperature rise rate and the temperature readings into respective fuzzy set categories; and

combine the respective fuzzy set categories into an output that indicates whether the hazardous condition exists or not.

16. The device according to claim 15 further comprising:

a classifier module configured to assign the classification values using a neural network, wherein the classification values lie in the range of 0 to 1.

17. The device according to claim 15 , wherein:

the plurality of sensors includes one or more of temperature sensors, smoke sensors, carbon monoxide sensors and infrared sensors.

18. The device according to claim 15 , wherein:

the fuzzy inference module triggers an alarm or another remedy if the fire exists.

19. The device of claim 15 , wherein the categorizing comprises:

assigning membership levels for one or more fuzzy set categories to the classification value;

determining a probability of the classification value belonging to the one or more fuzzy set categories; and

categorizing the classification value into a fuzzy set category for which the classification value has the highest probability.