A smart fire detection system using iot technology with automatic water sprinkler

Alqourabah, Hamood; Muneer, Amgad; Fati, Suliman Mohamed

doi:10.11591/ijece.v11i4.pp2994-3002

Cited by 48 publications

(29 citation statements)

References 25 publications

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“…In addition to this tool, it also has a GSM SIM 800L module that provides information to security agencies. An Arduino Uno microcontroller to facilitate the operation of the entire system controls it [18]. After conducting an investigation, the MQ-135 sensor detects smoke when it comes in contact with the sensor, and in addition to the MQ-135 sensor of the fire detection system using the fire detection system DFR0076, this module also fires up to a distance of 16 cm [19].…”

Section: Iot Based Gas Leakage Detection Systemmentioning

confidence: 99%

A Secured Model of IoT-based Smart Gas Detecting and Automatic Alarm System

Woishe

Sultana

Bristy

et al. 2022

IJCIS

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A gas leakage detector is a device for detecting gases in an area that is often used in a security system. This type of equipment is used to detect gas leakage or another emission. A gas warning device can alert operators in the vicinity of a possible gas leak and enable them to escape. The device is important because many gases can be harmful to organic life, such as humans or animals. This can be used to detect flammable, flammable, and toxic gases, as well as a lack of oxygen. Identifying potentially dangerous gas leaks through sensors. These sensors often use an audible alarm to alert people when dangerous gas has been detected. The purpose of this paper is to propose and discuss the design of an IoT-based gas leakage detection system that can automatically detect and warn gas leaks. The proposed system also includes a warning system for users. The system is based on sensors that can easily detect gas leaks.

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Section: Iot Based Gas Leakage Detection Systemmentioning

confidence: 99%

A Secured Model of IoT-based Smart Gas Detecting and Automatic Alarm System

Woishe

Sultana

Bristy

et al. 2022

IJCIS

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“…There are several different kinds of fire alarm systems developed by authors 1–3 to detect fire and various changes during fire. The authors in Reference 3 used a fuzzy logic and feedback control mechanism. An Adaptive neuro‐fuzzy Inference System was proposed by author 4 to compute the maximum likelihood of the real presence of fire and produces a fire alert.…”

Section: Related Workmentioning

confidence: 99%

“…There are several different kinds of fire alarm systems developed by authors [1][2][3] to detect fire and various changes during fire. The authors in Reference 3 used a fuzzy logic and feedback control mechanism.…”

Section: Related Workmentioning

confidence: 99%

A multimodel fire detection and alarm system for automobiles using internet of things and machine learning

Uma

Eswari

2022

Concurrency and Computation

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Fire accidents in vehicles lead to the loss of human lives. The fire detection and alarm systems are often error-prone and respond to nonactual indications of fire presence, known as false alarms. The proposed model detects the fire at the smoldering stage and buzzes an alarm if an actual fire or smoke is detected. This system can achieve this real alarm using multiple internet of things-based sensors, namely smoke/gas, flame, temperature, and a visualization camera. The visualization camera continuously captures images of the vehicle to check the existence of fire. Machine learning algorithms are executed on the sensor and image dataset to reduce false alarms and achieve high accuracy of results by using various performance metrics. K E Y W O R D Sfire detection and alarm system, flame sensor, gas sensor, internet of things, temperature sensor, visualization camera INTRODUCTIONLoss of human lives and economic losses are observed every year due to fire accidents. Many types of research were carried out to study the cause and explosion of fire and the efficient ways to control or prevent the fire outbreak in automobiles. Research findings state that most of the fire accident takes place during summer due to overheating of engine and other components. Use of old vehicle and low-maintenance vehicles is highly prone to get fire. Identified reasons for fire outbreaks are gas Leakage, electrical short circuit, electric car battery, AC problems, etc. The leakage of toxic gases due to car burning is hazardous.In recent days, the probability of fire accidents in vehicles has been higher, and it could be even more in electric cars. In fire detection, sensors are used to detect the fire; a single sensor cannot sense the fire effectively. It is high time to detect fire beforehand. Smoke is a significant sign for detecting early fire conditions. A number of fire detection systems were proposed in the past few years. Most approaches use different visual elements, including flame colors, motion, and geometrical contour. Integrated sensors work efficiently in Fire environments.These Integrated alarm systems allow fast identification, alarm alerts, and even fire extinguishing. This can be achieved by using integrated sensors.In this article, a fire detection and alarm system is proposed to detect fire in earlier stages. The proposed model uses integratedsensors and a camera for fire detection. Therefore, the proposed model avoids the rising of false alarm. The data is collected from the sensors such as smoke, temperature, and flame and are used to train the machine using the machine learning algorithms. Similarly, the image patterns of smoke and flame are also collected and used to train the machine. Therefore, when the fire is detected, the alarm will be buzzed.The remainder of the article is organized as follows: Section 2 discusses the related work. Section 3 presents the proposed system. Section 4 elucidates the components of the proposed architecture. Section 6 confers the efficiency of the proposed system and discusses the ...

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“…An review of various relevant Internet -of -things intelligent fire detection and management works is provided in this section. Reference [15] utilized numerous sensors to gather real-time readings. When an emergency arises, sensor data are examined to start a sprinkler system.…”

Section: B Internet Of Things (Iot)mentioning

confidence: 99%

An IoT-based Fire Safety Management System for Educational Buildings: A Case Study

Kamel¹,

Jamal²,

Omri³

et al. 2022

IJACSA

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Safety is a serious concern that should be addressed carefully in different locations including homes, workplaces and educational buildings. The risk of fire is the most significant threat in many educational facilities such as schools, universities, offices, etc. The main goal of this work is developing an effective system that allows early managing of fires to avoid material and human losses. With the advent of the Internet of Things (IoT), the implementation of such system became possible. A low-cost system incorporating IoT sensors is constructed in this study to collect data (heat, the number of people at the fire scene, ...) in real time. The system provides a control panel that displays readings from all sensors on a single web page. When the collected values exceed a particular threshold, the system sends a message to the building keeper's phone, allowing him to notify the authorities or dispatch firemen in real time. One of the system's most important characteristics is that it keeps track of how many people are at the fire scene, simplifying the evacuation process and allowing civil defense authorities to efficiently manage resources. The system has been successfully tested in a variety of circumstances in an educational building (Al-Faisaliah female campus,

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A smart fire detection system using iot technology with automatic water sprinkler

Cited by 48 publications

References 25 publications

A Secured Model of IoT-based Smart Gas Detecting and Automatic Alarm System

A Secured Model of IoT-based Smart Gas Detecting and Automatic Alarm System

A multimodel fire detection and alarm system for automobiles using internet of things and machine learning

An IoT-based Fire Safety Management System for Educational Buildings: A Case Study

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