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

Fast and Accurate Event Detection Based on Wireless Sensor Networks Using Fuzzy Logic Method

2013 ◽  
Vol 300-301 ◽  
pp. 523-526
Author(s):  
Wen Tsai Sung ◽  
Jui Ho Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Event Detection ◽  
Detection System ◽  
Environmental Parameters ◽  
Fire Detection ◽  
Critical Issue ◽  
Wireless Sensor ◽  
Detection Techniques

Wireless Sensor Networks have recently been used for environmental monitoring and real time event detection because of their low implementation costs and distributed sensing and processing capabilities. Event detection is a critical issue in wireless sensor networks. Fire detection is used as an example in our event detection system. Algorithms are required to detect fire sensors and measure the environmental parameters (temperature, humidity, light intensity, and Carbon Monoxide) to determine if a fire is present or not. It is urgent to research fire detection techniques that are efficient, convenient and practical. Although there are several works on fire detection using WSNs, sufficient attention has rarely been paid to using fuzzy logic methods. We present a novel approach based on fuzzy logic for multi-sensors data fusion in a wireless sensor network system with a node-sink mobile network structure to detect fire. Through simulation results, it is shown that the proposed innovative fuzzy logic algorithm can improve the reliability and accuracy of sensed information and reduce the rate of false alarm.

scholarly journals Computer Vision Application for Early Stage Smoke Detection on Ships

2016 ◽  
Vol 52 (1) ◽  
pp. 63-80
Author(s):  
Miroslav Bistrović ◽  
Jasmin Čelić ◽  
Domagoj Komorčec
Keyword(s):  
Detection System ◽  
Early Stage ◽  
Fire Detection ◽  
Water Mist ◽  
Smoke Detector ◽  
Smoke Detection ◽  
Engine Room ◽  
Computer Image Processing ◽  
Flame Detector ◽  
Safety Features

Nowadays, ship’s engine room is fire protected by automatic fire fighting systems, usually controlled from a place located outside the engine room. In order to activate the water mist extinguishing system automatically, at least two different fire detectors have to be activated. One of these detectors is a flame detector that is not hampered by various air flows caused by ventilation or draft and is rapidly activated and the other is smoke detector which is hampered by these flows causing its activation to be delayed. As a consequence, the automatic water mist extinguishing system is also delayed, allowing for fire expansion and its transfer to surrounding rooms. In addition to reliability of the ship’s fire detection system as one of the crucial safety features for the ship, cargo, crew and passengers, using a systematic approach in this research the emphasis is placed on the application of new methods in smoke detection such as the computer image processing and analysis, in order to achieve this goal. This paper describes the research carried out on board ship using the existing marine CCTV systems in early stages of smoke detection inside ship’s engine room, which could be seen as a significant contribution to accelerated suppression of unwanted consequences.

scholarly journals Smart Fire Detection and Deterrent System for Human Savior by Using Internet of Things (IoT)

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5500
Author(s):  
Abdul Rehman ◽  
Muhammad Ahmed Qureshi ◽  
Tariq Ali ◽  
Muhammad Irfan ◽  
Saima Abdullah ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Internet Of Things ◽  
Fire Detection ◽  
Monitoring Systems ◽  
Sensor Systems ◽  
Fire Alarm ◽  
Fuzzy Logic Algorithm ◽  
Fire Monitoring ◽  
Rule Set ◽  
Single Sensor

Fire monitoring systems have usually been based on a single sensor such as smoke or flame. These single sensor systems have been unable to distinguish between true and false presence of fire, such as a smoke from a cigarette which might cause the fire alarm to go off. Consuming energy all day long and being dependent on one sensor that might end with false alert is not efficient and environmentally friendly. We need a system that is efficient not only in sensing fire accurately, but we also need a solution which is smart. In order to improve upon the results of existing single sensor systems, our system uses a combination of three sensors to increase the efficiency. The result from the sensor is then analyzed by a specified rule-set using an AI-based fuzzy logic algorithm; defined in the purposed research, our system detects the presence of fire. Our system is designed to make smart decisions based on the situation; it provides feature updated alerts and hardware controls such as enabling a mechanism to start ventilation if the fire is causing suffocation, and also providing water support to minimize the damage. The purposed system keeps updating the management about the current severity of the environment by continually sensing any change in the environment during fire. The purposed system proved to provide accurate results in the entire 15 test performed around different intensities of a fire situation. The simulation work for the SMDD is done using MATLAB and the result of the experiments is satisfactory.

scholarly journals Internet of Things: A Comprehensive Study on Machine Learning-based Intrusion Detection approaches

2021 ◽  
Author(s):  
Priyanka Gupta ◽  
Lokesh Yadav ◽  
Deepak Singh Tomar
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Real Time ◽  
Detection System ◽  
Research Work ◽  
Security And Privacy ◽  
Iot Security ◽  
Advantages And Disadvantages ◽  
Iot Devices

The Internet of Things (IoT) connects billions of interconnected devices that can exchange information with each other with minimal user intervention. The goal of IoT to become accessible to anyone, anytime, and anywhere. IoT has engaged in multiple fields, including education, healthcare, businesses, and smart home. Security and privacy issues have been significant obstacles to the widespread adoption of IoT. IoT devices cannot be entirely secure from threats; detecting attacks in real-time is essential for securing devices. In the real-time communication domain and especially in IoT, security and protection are the major issues. The resource-constrained nature of IoT devices makes traditional security techniques difficult. In this paper, the research work carried out in IoT Intrusion Detection System is presented. The Machine learning methods are explored to provide an effective security solution for IoT Intrusion Detection systems. Then discussed the advantages and disadvantages of the selected methodology. Further, the datasets used in IoT security are also discussed. Finally, the examination of the open issues and directions for future trends are also provided.

scholarly journals Water Discharge and River Depth Measurement Using Fuzzy Logic Based on Internet of Things

2020 ◽  
Vol 4 (3) ◽  
pp. 384-391
Author(s):  
Kurnia Wisuda Aji ◽  
Aji Gautama Putrada ◽  
Sidik Prabowo ◽  
Mas'ud Adhi Saputra
Keyword(s):  
Fuzzy Logic ◽  
Internet Of Things ◽  
Real Time ◽  
Water Flow ◽  
Water Discharge ◽  
Ultrasonic Sensor ◽  
Flow Sensor ◽  
Depth Information ◽  
Sufficient Information ◽  
Depth Measurement

Based on statistics from Indonesian National Board for Disaster Management (BNPB) there are still many casualties caused by drifting or drowning in rivers every year. This is because most victims do not have sufficient information related to water discharge and river depth. In an effort to reduce the potential victims of these problems, a prototype was designed to provide a warning regarding river status as a display in the detail condition of the river in real-time. In this research, a prototype measuring instrument was produced that could provide information on water discharge and river depth in a sustainable and real-time manner. The prototype device consists of two main sensors as an implementation of internet of things, a water flow sensor and an ultrasonic sensor. Water flow sensor used to calculate the water discharge, and ultrasonic sensor used to measure depth of the river. Fuzzy logic has been used because it can work well for simple classification and work similarly like human reasoning. This information can be monitored through the website and LCD attached on the device. The results of the study with the help of the Linear Congruential Generator (LCG) method indicated that greater input value of the water discharge and the river depth caused more dangerous of the river status. Whereas the prototype produced has an error range of 5-6 cm for depth information generated by the ultrasonic sensor while the accuracy of the water flow sensor on the master device is 79.75% and the slave device is 84%.  

scholarly journals IOTFlood: hardware and software platform using internet of things to monitor floods in real time

2021 ◽  
Vol 16 (4) ◽  
pp. 1
Author(s):  
Francisco Vital Da Silva Júnior ◽  
Mônica Ximenes Carneiro Da Cunha ◽  
Marcílio Ferreira De Souza Júnior
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Monitoring System ◽  
Research Design ◽  
Open Source Software ◽  
Low Cost ◽  
Sensor Data ◽  
Software Platform ◽  
Web Interface ◽  
Iot Platform

Floods are responsible for a high number of human and material losses every year. Monitoring of river levels is usually performed with radar and pre-configured sensors. However, a major flood can occur quickly. This justifies the implementation of a real-time monitoring system. This work presents a hardware and software platform that uses Internet of Things (IoTFlood) to generate flood alerts to agencies responsible for monitoring by sending automatic messages about the situation of rivers. Research design involved laboratory and field scenarios, simulating floods using mockups, and later tested on the Mundaú River, state of Alagoas, Brazil, where flooding episodes have already occurred. As a result, a low-cost, modular and scalable IoT platform was achieved, where sensor data can be accessed through a web interface or smartphone, without the need for existing infrastructure at the site where the IOTFlood solution was installed using affordable hardware, open source software and free online services for the viewing of collected data.

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