Hardware Design and Web-Based Communication Modules of a Real-Time Multisensor Fire Detection and Notification System Using Fuzzy Logic

2017 ◽  
Vol 53 (1) ◽  
pp. 559-566 ◽  
Author(s):  
Robert A. Sowah ◽  
Abdul R. Ofoli ◽  
Selase N. Krakani ◽  
Seth Yayra Fiawoo
Keyword(s):  
Fuzzy Logic ◽  
Real Time ◽  
Hardware Design ◽  
Fire Detection ◽  
Web Based ◽  
Notification System

scholarly journals Hardware Module Design and Software Implementation of Multisensor Fire Detection and Notification System Using Fuzzy Logic and Convolutional Neural Networks (CNNs)

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Robert A. Sowah ◽  
Kwaku Apeadu ◽  
Francis Gatsi ◽  
Kwame O. Ampadu ◽  
Baffour S. Mensah
Keyword(s):  
Neural Networks ◽  
Fuzzy Logic ◽  
Convolutional Neural Networks ◽  
Fire Detection ◽  
Web Based ◽  
Notification System ◽  
Multisensor Data Fusion ◽  
Standard Fire ◽  
Area Of Interest ◽  
Detection Technology

This paper presents the design and development of a fuzzy logic-based multisensor fire detection and a web-based notification system with trained convolutional neural networks for both proximity and wide-area fire detection. Until recently, most consumer-grade fire detection systems relied solely on smoke detectors. These offer limited protection due to the type of fire present and the detection technology at use. To solve this problem, we present a multisensor data fusion with convolutional neural network (CNN) fire detection and notification technology. Convolutional Neural Networks are mainstream methods of deep learning due to their ability to perform feature extraction and classification in the same architecture. The system is designed to enable early detection of fire in residential, commercial, and industrial environments by using multiple fire signatures such as flames, smoke, and heat. The incorporation of the convolutional neural networks enables broader coverage of the area of interest, using visuals from surveillance cameras. With access granted to the web-based system, the fire and rescue crew gets notified in real-time with location information. The efficiency of the fire detection and notification system employed by standard fire detectors and the multisensor remote-based notification approach adopted in this paper showed significant improvements with timely fire detection, alerting, and response time for firefighting. The final experimental and performance evaluation results showed that the accuracy rate of CNN was 94% and that of the fuzzy logic unit is 90%.

scholarly journals Sistem Pemantauan dan Pendeteksi Kebakaran berbasis Logika Fuzzy dan Real-time Database

2021 ◽  
Vol 9 (3) ◽  
pp. 577
Author(s):  
EVA AISAH HW ◽  
ROHMAT TULLOH ◽  
SUGONDO HADIYOSO ◽  
DADAN NUR RAMADAN
Keyword(s):  
Fuzzy Logic ◽  
Internet Of Things ◽  
Real Time ◽  
Human Error ◽  
Detection System ◽  
Environmental Parameters ◽  
Fire Detection ◽  
Smoke Detector ◽  
Web Interface ◽  
Average Transmission

ABSTRAKKebakaran rumah seringkali disebabkan oleh kelalaian manusia. Oleh karena itu diperlukan sebuah sistem yang dapat mendeteksi kebakaran secara online realtime. Pada studi ini, dirancang dan diimplementasikan sebuah sistem pendeteksi kebakaran dengan sejumlah sensor untuk mengukur beberapa parameter lingkungan. Sistem ini dilengkapi dengan pengambil keputusan menggunakan metode fuzzy logic. Parameter lingkungan yang diukur mencakup suhu ruangan, asap dan api yang kemudian dapat dimonitor secara real-time melalui web interface menggunakan Internet of Things platform. Pengujian menunjukkan bahwa detektor dapat mendeteksi api dengan jarak hingga 100 cm dengan akurasi mencapai 100%. Pengujian sensor suhu menunjukkan akurasi 98.79%, sementara itu detektor asap memperoleh akurasi 77.81%. Sistem ini mampu mengirimkan data dengan rata-rata delay transmisi 0.62 detik. Sistem usulan ini diharapkan dapat menyediakan pemantauan kondisi suatu ruangan secara real-time.Kata kunci: Kebakaran, Real-Time, Deteksi, Fuzzy, Internet Of Things ABSTRACTHouse fires are often caused by human error. Therefore, we need a system that can detect fires online real-time. In this study, a fire detection system with a number of sensors is designed and implemented to measure several environmental parameters. This system is equipped with a decision maker using the fuzzy logic method. The environmental parameters measured include room temperature, smoke and fire which can then be monitored in real time via a web interface using the Internet of Things platform. Tests show that the detector can detect fires with a distance of up to 100 cm with an accuracy of up to 100%. The temperature sensor test shows an accuracy of 98.79%, while the smoke detector generates an accuracy of 77.81%. This system is capable of sending data with an average transmission delay of 0.62 seconds. This proposed system is expected to provide realtime monitoring of the condition of a room.Keywords: Fire, Real-time, detection, Fuzzy, internet of things

A Real-Time Fire Detection and Notification System Based on Computer Vision

2013 ◽  
Author(s):  
Sahar Bayoumi ◽  
Elham AlSobky ◽  
Moneerah Almohsin ◽  
Manahel Altwaim ◽  
Monira Alkaldi ◽  
...  
Keyword(s):  
Computer Vision ◽  
Real Time ◽  
Fire Detection ◽  
Notification System
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