A Fire-Detection and Control System in Automobiles: Implementing a Design That Uses Fuzzy Logic to Anticipate and Respond

2019 ◽  
Vol 25 (2) ◽  
pp. 57-67 ◽  
Author(s):  
Robert Sowah ◽  
Kwame O. Ampadu ◽  
Abdul R. Ofoli ◽  
Koudjo Koumadi ◽  
Godfrey A. Mills ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fire Detection ◽  
And Control

Neural Networks and Fuzzy Logic in Electrical Engineering Control Courses

2003 ◽  
Vol 40 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Francisco Jurado ◽  
Antonio Caño ◽  
Manuel Ortega
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Intelligent Systems ◽  
Fuzzy Logic Controllers ◽  
Analysis And Design ◽  
Modelling Analysis ◽  
Systems And Control ◽  
And Control ◽  
Theoretical Developments ◽  
Logic Controllers

Control system education must include experimental exercises that complement the theory presented in lectures. These exercises include modelling, analysis and design of a control system. Key concepts and techniques in the area of intelligent systems and control have been discovered and developed over the past few decades. While some of these methods have significant benefits to offer, engineers are often reluctant to utilise new intelligent control techniques, for several reasons. In this paper fuzzy logic controllers have been developed using speed and mechanical power deviations, and a neural network has been designed to tune the gains of the fuzzy logic controllers. Student feedback indicates that theoretical developments in lectures on control systems were only appreciated after the laboratory exercises.

scholarly journals Development of Structure of Intellectual Information Measuring and Control System of Control of Chlorine Dosing and Chloroform Content in Drinking Water

2020 ◽  
Vol 17 (4) ◽  
pp. 48
Author(s):  
A. I. Yuhno ◽  
N. K. Plugotarenko
Keyword(s):  
Fuzzy Logic ◽  
Drinking Water ◽  
Control System ◽  
Information Measuring ◽  
And Control

Защита здоровья человека от канцерогенных рисков, а также обеспечение эффективности систем водоснабжения являются важной задачей на сегодняшний день. В связи с этим в данной работе рассмотрены вопросы применения метода контроля качества питьевой воды на базе нейросетевых технологий и методов искусственного интеллекта. В основу предложенного метода положен алгоритм нечеткого вывода Мамдани. Предложены параметры качества воды, применяемые в качестве лингвистических переменных алгоритма нечеткого вывода. Данный метод реализуется интеллектуальной информационно-измерительной и управляющей системой контроля дозирования хлорагента и содержания хлороформа на станциях водоподготовки в режиме реального времени. Разработка системы осуществлялась с использованием программного комплекса MatLab, а именно пакета нечеткого моделирования Fuzzy Logic Toolbox. Разработана структура интеллектуальной информационно-измерительной и управляющей системы. Построение информационно-измерительной системы дозирования хлорагента основывалось на принципах минимизации риска для здоровья населения. Сделаны выводы, позволяющие оценить влияние разработанной системы на повышение качества питьевой воды. Апробация работы системы позволила отразить эффективность ее применения: снижение избыточного хлорирования и канцерогенного риска образования побочных продуктов обеззараживания питьевой воды относительно применяемых на данный момент на типовых станциях водоподготовки систем контроля.

scholarly journals PROTOTYPE SISTEM KENDALI KADAR KEPEKATAN ASAP PADA SMOKING ROOM DENGAN METODE FUZZY LOGIC BERBASIS ARDUINO

2020 ◽  
Vol 3 (2) ◽  
pp. 32-37
Author(s):  
M. Sunan Ishfahani ◽  
Nur Hanifah Yuninda ◽  
Purwanto Gendroyono
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Research And Development ◽  
Fuzzy Logic Controller ◽  
Concentration Level ◽  
Requirements Analysis ◽  
Smoke Detection ◽  
Fuzzy Logic Method ◽  
Analysis Design ◽  
And Control

The purpose of this research is to make prototype of smoke concentration levels control system in smoking room by fuzzy logic method based on arduino. The prototype is able to detect and control the smoke to stay constantly in allowed threshold to the smoking room and provide periodic information about the concentration level in that smoking room automatically. This research uses Research and Development Method, which includes requirements analysis, design, basic implementation into prototype form. Requirements analysis is based on the lack of smoke detection and control systems in smoking rooms. The design of the control system in this study is applied to fuzzy logic controller. This research emphasizes more on the basic implementation of the desired prototype by standards testing such as output voltage testing and fuzzyfication testing that have not arrived at the stage of efficiency testing. The results show that the system will be put into danger condition if the concentration of smoke reaches 80 PPM. At that level, the voltage measured by the sensor is in the range of 3.19 to 3.41 VDC with an average voltage increase of 0.035 to 0.04 VDC per PPM. Error in fuzzyfication testing is 0.04% and 0.08% based on calculation. Abstrak Tujuan penelitian ini adalah membuat prototype sistem kendali kadar kepekatan asap pada smoking room dengan metode fuzzy logic berbasis arduino. Alat ini dapat mendeteksi dan mengendalikan asap agar tetap pada ambang batas yang diperbolehkan pada smoking room serta memberikan informasi secara periodik tentang kadar kepekatan asap yang terdapat pada smoking room secara otomatis. Penelitian ini menggunakan Metode Penelitian dan Pengembangan (Research and Development) yang meliputi analisis kebutuhan, perancangan, implementasi dasar dalam bentuk prototype dan pengujian. Analisis kebutuhan didasari karena jarang terdapatnya sistem deteksi dan kendali asap pada smoking room. Perancangan sistem kendali pada penelitian ini diterapkan fuzzy logic controller. Penelitian ini lebih menekankan pada implementasi dasar dari prototype yang diinginkan dengan pengujian standar seperti pengujian tegangan keluaran dan pengujian fuzzyfikasi yang belum sampai pada tahap pengujian efisiensi. Hasil penelitian menunjukkan bahwa sistem akan mengindikasikan sebuah bahaya jika kadar kepekatan asap mencapai 80 PPM. Pada kadar tersebut, tegangan yang terukur oleh sensor berada pada kisaran 3,19 sampai 3,41 VDC dengan rata-rata kenaikan tegangan sebesar 0,035 sampai 0,04 VDC per PPM. Error pada pengujian fuzzyfikasi adalah sebesar 0,04 % dan 0,08 % yang didasarkan pada perhitungan.

scholarly journals Design of an IoT-Based Fuzzy Approximation Prediction Model for Early Fire Detection to Aid Public Safety and Control in the Local Urban Markets

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1391
Author(s):  
Emmanuel Lule ◽  
Chomora Mikeka ◽  
Alexander Ngenzi ◽  
Didacienne Mukanyiligira
Keyword(s):  
Fuzzy Logic ◽  
Prediction Model ◽  
Fire Safety ◽  
Public Safety ◽  
Fire Detection ◽  
Safety Monitoring ◽  
Fire Intensity ◽  
Urban Markets ◽  
And Control ◽  
Early Fire Detection

Fire monitoring in local urban markets within East Africa (EA) has been seriously neglected for a long time. This has culminated in a severe destruction of life and property worth millions. These rampant fires are attributed to electrical short circuits, fuel spillages, etc. Previous research proposes single smoke detectors. However, they are prone to false alarm rates and are inefficient. Also, satellite systems are expensive for developing countries. This paper presents a fuzzy model for early fire detection and control as symmetry’s core contribution to fuzzy systems design and application in computer and engineering sciences. We utilize a fuzzy logic technique to simulate the performance of the model using MATLAB, using six parameters: temperature, humidity, flame, CO, CO2 and O2 vis-à-vis the Estimated Fire Intensity Prediction (EFIP). Results show that, using fuzzy logic, a significant improvement in fire detection is observed with an overall accuracy rate of 95.83%. The paper further proposes an IoT-based fuzzy prediction model for early fire detection with a goal of minimizing extensive damage and promote intermediate fire suppression and control through true fire incidences. This solution provides for future public safety monitoring, and control of fire-related situations among the market community. Hence, fire safety monitoring is significant in providing future fire safety planning, control and management by putting in place appropriate fire safety laws, policies, bills and related fire safety practices or guidelines to be applied in public buildings, market centers and other public places.

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