%0 Journal Article %1 noauthororeditor %A Umoh, Uduak %A Inyang, Udoinyang G. %A Nyoho, Emmanuel E. %D 2019 %J International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI) %K Algorithm Detection Environmental Fire Fuzzy Interval Logic Outbreak Parameter Reduction Type Type-2 %N 3 %P 13 %R DOI :10.5121/ijscai.2019.8303 %T INTERVAL TYPE-2 FUZZY LOGIC FOR FIRE OUTBREAK DETECTION %U http://aircconline.com/ijscai/V8N3/8319ijscai02.pdf %V 8 %X This paper employed an Interval Type-2 Fuzzy Logic (IT2FL) in the detection of fire outbreak using environmental parameters. Fire outbreak data capturing device (FODCD) is developed and used in capturing environmental parameter values. The FODCD is comprised of DHT11 temperature sensor, MQ-2 smoke sensor, LM393 Flame sensor, and ESP8266 Wi-Fi module connected to Arduino nano v3.0.board. An android application is developed using Android Studio 3.0 to test the functionality of the system. Experimental result indicates that, with the temperature value of 40.657oC, Smoke value of 77.86%, and Flame value of 762.95ppm (part per million), with a threshold T = 0.8, the IT2FL predicted fire outbreak at 0.778 (78%). IT2FL is evaluated using the True Positive Rate (TPR), False Positive Rate (FPR), Accuracy, Error Rate (ER), Precision, and Recall performance metrics. The performance result shows that, the system performs optimally when threshold T is kept between an optimal range of 0.8 and 0.85.

@article{noauthororeditor, abstract = {This paper employed an Interval Type-2 Fuzzy Logic (IT2FL) in the detection of fire outbreak using environmental parameters. Fire outbreak data capturing device (FODCD) is developed and used in capturing environmental parameter values. The FODCD is comprised of DHT11 temperature sensor, MQ-2 smoke sensor, LM393 Flame sensor, and ESP8266 Wi-Fi module connected to Arduino nano v3.0.board. An android application is developed using Android Studio 3.0 to test the functionality of the system. Experimental result indicates that, with the temperature value of 40.657oC, Smoke value of 77.86%, and Flame value of 762.95ppm (part per million), with a threshold T = 0.8, the IT2FL predicted fire outbreak at 0.778 (78%). IT2FL is evaluated using the True Positive Rate (TPR), False Positive Rate (FPR), Accuracy, Error Rate (ER), Precision, and Recall performance metrics. The performance result shows that, the system performs optimally when threshold T is kept between an optimal range of 0.8 and 0.85.}, added-at = {2019-09-13T11:08:43.000+0200}, author = {Umoh, Uduak and Inyang, Udoinyang G. and Nyoho, Emmanuel E.}, biburl = {https://www.bibsonomy.org/bibtex/214fc720f251b46374f757a8e7933f06a/leninsha}, doi = {DOI :10.5121/ijscai.2019.8303}, interhash = {bc11e991c25358b37eb69551a55af109}, intrahash = {14fc720f251b46374f757a8e7933f06a}, issn = {2319 - 1015}, journal = {International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)}, keywords = {Algorithm Detection Environmental Fire Fuzzy Interval Logic Outbreak Parameter Reduction Type Type-2}, language = {English}, month = {August}, number = 3, pages = 13, timestamp = {2019-09-13T11:08:43.000+0200}, title = {INTERVAL TYPE-2 FUZZY LOGIC FOR FIRE OUTBREAK DETECTION}, url = {http://aircconline.com/ijscai/V8N3/8319ijscai02.pdf}, volume = 8, year = 2019 }