Fire Detection System Research Articles

Enhanced fire sprinkler system: Fiber optical monitoring of fire sprinkler heads

A novel fiber optical monitoring concept for real-time localization of activated fire sprinkler heads is presented and discussed in this work. The concept is implemented by a designed fiber optical sensor and standard telecom components, such as optical time-domain reflectometer (OTDR), single-mode glass fiber, couplers, and reflectors. The proposed sensor based on optic reflection and interrupting mechanism allows to monitor the current status of sprinkler head and to differentiate the sprinkler activation from unwanted interferences, for example, glass fiber breakage. According to the experiments and calculations, hundreds of sprinkler heads can be monitored by a single OTDR device that results in net system energy consumption well below 100 mW per sensor point. The proposed monitoring concept opens up new perspectives for applying fiber optical sensors in fire protection methods. It can be used as a self-contained sensor network or in combination with modern fire detection and alarm systems in a primary-secondary-configuration.

A comprehensive review on fire damage assessment of reinforced concrete structures

The provision of appropriate fire-safety measures is a basic need in building design to guarantee the safety of its occupants. Damage due to fire is one of the most destructive aspects that cause deterioration of reinforced concrete structures. Although concrete is a noncombustible material, its physical, chemical, and mechanical characteristics degrade if exposed to a high temperature. The seriousness of a fire in concrete structures is mostly determined by the magnitude and duration of the fire. If the magnitude of fire is minor and for a limited time then the damage to the concrete members is likely to be minimal. Similarly, a higher magnitude or high temperature with a longer duration will cause maximum damage or may result in the collapse of concrete structures. The purpose of this review is to summarize the damage of reinforced concrete (RC) structures after a severe occurrence of fire. Additionally, to discuss the firefighting deficiencies, and remedial measures adopted for recovering the damage due to fire in high-rise buildings. The current study is a review of previous studies from the last decade on important fire damage assessment measures used for damage assessment of RC structures. Some case studies have also been reported in this work. The review results show the popularity of surveys and case studies on fire damage related to RC structures. The essential contributing factors are collected that correspond to the damage of RC structures due to fire. The electrical problems, faulty fire detection systems, and a lack of firefighting equipment, and obstacles in emergency exits were shown to be the most frequent causes of fire damage.

Identification of Parameters Required to Reduce Emergency Response Time for An Integrated Facility

In an emergency incident time is of the crucial factor, and the basic philosophy of an emergency response agency is to respond as quickly as possible to minimize the loss of life and property damage. Emergency response operations are very important activities in the oil and gas industrial areas. As an incident in an integrated facility at oil and gas industrial area can have considerable major economic and social impact, response to such an incident must be provided in a very short time. The use of parameters plays an important role in the successful implementation of emergency response. This case study considered configuration emergency response time parameters at an integrated facility. Therefore, to predict the response time consideration must be given to the characteristics of emergency response parameters, its effectiveness and efficiency. The decisions for such emergency responses to integrated facility should consider the available emergency resources, and other factors such as emergency responders’ competency, fire protection and fire detection system, and the characteristics of surrounding affected industrial facilities. Pilot Test results showed that the top five most parameters affecting emergency response time at the case study of oil and gas integrated facility were namely location, competency, road access, emergency vehicle and frequent drill/exercise. Other analyses resulted that emergency drills and exercises parameter shall be critically examined. Drills constitute a simultaneous and comprehensive test of emergency plans, staffing levels, personnel training, procedures, facilities, equipment, and materials. Having this process, the company able to improve emergency preparedness and response management and aligned with crisis management protocol by government authority.

Intelligent Multi-Sensor Detection System for Monitoring Indoor Building Fires

This paper presents a novel fire detection system to monitor various types of indoor building fires. While conventional studies mainly focus on developing fire sensing systems or detection algorithms, the proposed fire detection system integrates both sensing and detection phases to effectively utilize diverse sensor signals in real-time and detect fire outbreak at an early stage. The proposed fire sensing system gathers sensor data from multiple sensor types that are sensitive to measuring various components emitted from fires. Then, the collected sensor data are utilized by a similarity matching-based fire detection algorithm that captures diverse shape patterns that exist in the sensor signals under various fire scenarios, and detects the outbreak of fires at an early stage, with low false alarms. The real-life sensor data collected by the newly developed sensing system and experimental results conducted by the proposed fire detection algorithm show the effectiveness of the proposed fire detection system.

Android mobile application for wildfire reporting and monitoring

Peat fires cause major environmental problems in Central Kalimantan Province, Indonesia and threaten human health and effect the social-economic sector. The lack of peat fire detection systems is one factor that causing these reoccurring fires. Therefore, in this study, we develop an Android mobile platform application and a web-based application to support the citizen-volunteers who want to contribute wildfires reports, and the decision-makers who wish to collect, visualize, and evaluate these wildfires reports. In this paper, the global navigation satellite system (GNSS) and a global position system (GPS) sensor from a smartphone’s camera, is a useful tool to show the potential fire and smoke’s close-range location. The exchangeable image (EXIF) file image and GPS metadata captured by a mobile phone can store and supply raw observation to our devices and sent it to the data center through global internet communication. This work’s results are the proposed application easy-to-use to monitoring potential peat fire by location and data activity. This paper focuses on developing an application for the mobile platform for peat fire reporting and a web-based application to collect peat fire location for decision-makers. Our main objective is to detect the potential and spread of fire in peatlands as early as possible by utilizing community reports using smartphones.

GSM Based SMS Alert Fire Alarm System

Abstract: The design of a fire alarm with Arduino-based system by means of GSM Module. The work purposely for house safety where the main point is to avoid the fire accidents occurred to the residents and the properties inside the house. In order to prevent losses accrued from fire accidents, various alarm systems have been developed such as smoke detectors, temperature sensor based systems etc. The design and implementation of a cost effective and reliable GSM based SMS Alert fire alarm system. The device will be able to monitor the temperature of the environment, the smoke level, send SMS alert to an inbuilt GSM number. When the system detects the temperature of 100C or more, it will immediately display an alert notification on LCD display and simultaneously sending an SMS alert to the users upon the high raise temperature in the house. This fire detection system consists of a smoke sensor, buzzer, LCD display and GSM module is interfaced with Arduino board. Keywords: Smoke sensor, GSM Module, Arduino, LED display, Buzzer

Real-Time Monitoring: Development of Low Power Fire Detection System for Dense Residential Housing Based on Internet of Things (IoT) and Cloud Messenger

Purpose: This paper reports on the development of a low-power fire potential monitoring system for densely populated housing based on IoT Study design: This system consists of sensors integrated with a microcontroller and a Wi-Fi module that can provide data in real-time and can be accessed remotely. In addition, this system has also been simulated to analyze environmental conditions as notification data sent using cloud messenger. The grouping of potential fire hazards based on the legibility of physical parameter values is also displayed. Findings: In performance measurement, the data loss of this system is less than 1% of the total data every day. Value: It shows that this system is feasible and applied more broadly to anticipate fires in densely populated areas.

Numerical Analysis of Smoke Behavior and Detection of Solid Combustible Fire Developed in Manned Exploration Module Based on Exploration Gravity

A fire during manned space exploration can cause serious casualties and disrupt the mission if the initial response is delayed. Therefore, measurement technology that can detect fire in the early stage of ignition is important. There have been a number of works that investigate the smoke behaviors in microgravity as the foundation for a reliable method for sensing a fire during spaceflight. For space missions to the outer planets, however, a strategy of detecting smoke as an indicator of fire should be adjusted to cover the fire scenario that can be greatly affected by changes in gravity (microgravity, lunar, Mars, and Earth gravity). Therefore, as a preliminary study on fire detectors of the manned pressurized module, the present study examined the smoke particle behavior and detection characteristics with respect to changes in gravity using numerical analysis. In particular, the effects of the combination of buoyancy and ventilation flow on the smoke particle movement pattern was investigated to further improve the understanding of the fire detection characteristics of the smoke detector, assuming that a fire occurred in different gravity environments inside the pressurized module. To this end, we modeled the internal shape of Destiny and performed a series of numerical analysis using the Fire Dynamics Simulator (FDS). The findings of this study can provide basic data for the design of a fire detection system for manned space exploration modules.

Automatic Fire Detection and Extinction with Infrared Multispectrum Electro-Optical Technology with Watch-Dog Timer Control, for a 220KV to 33KV Transformer

The present research aims to design an automatic fire detection and extinction system, developed with infrared multi-spectrum electro-optical technology with watch-dog timer control, for an electrical transformer from 220KV to 33KV. Upon its development, it is concluded that the automatic detection and extinction system has a deluge system with sprayed water, which will be activated by a detection system with flame sensors, this system has infrared multispectrum Electro-Optical Technology and will be controlled by through the Timer Watch-Dog, which will automatically detect and report any failure in the state-of-theart microprocessor. By subjecting the detection and extinguishing system to operational and functional tests, an optimal response of the deluge sprinklers was obtained, through the pressure and flow parameters, also a coefficient of determination R2 equal to 0.991 is obtained, which represents that the design is optimal, evidencing feasibility from the operational and functional point of view. Keywords— Detection, Extinction, Automatic, ElectroOptical, Multispectral, Infrared, Timer Watch-Dog, Transformer

Design of a Home Fire Detection System Using Arduino and SMS Gateway

Fire is a problem that can happen at any time. Delay in coping with house fires can induce in loss of human life or material. If the fire is not held severely, incidents like house fires can occur and create more significant losses, especially with the increasing number of residents’ settlements in the formation of huddled houses, which will be more challenging to handle in case of a fire. This research aims to build a prototype system that quickly helps house owners and firefighters to detect fires and gas leaks. This home fire detection system is utilized to measure room temperature and gas levels in a room, then the output of this system is sending information of short messages and alarms. The results revealed that the prototype room with a scale of 1:25, 1:50, and 1:75 which uses a temperature sensor and a gas sensor could run as desired. In 10 testing trials, the system works according to the designed plan, which means the system could interpret the temperature and gas leakage of a room, then the system will send a short message and ring the alarm.

Real Time Fire Detection System with Image Processing

Fire detectionsystemby image processing is a growing research in this era. There are many methods used to detect fire out, butstill need to develop an accurate method to detect fire without false alarms. This is due to the fact that many methods used RGB colour mode for detection. In this paper, mainly focuson detecting the fire effectively using thermal video from a thermal camera while in the same time the system will alert the people if fire was detected,and also observed the speed of the fire.This will enormouslybenefitto the fire fighters.With thissystem, thefire can be detected effectively while alerting the people and giving valuable information to the fire fighters fortheir job more effectively.

Autonomous robotic fire detection and extinguishing system

Firefighting is a dangerous job with a high death rate. Robotics is the new way to protect the environment and human lives. This work proposes an autonomous robot system that can inevitably discover fire using the flame sensor and extinguish it. This project includes Arduino UNO, flame sensor, servo motor, motor driver, relay module, Bluetooth HC-06 module, and water pump. Besides, using the push Bluetooth app at the transmitting end, commands are sent to the receiver to control the robot’s movement. The motors are connected to the microcontroller and used to move the robot and sprinkle water on the fire. A water tank and a water pump are mounted on the robot body and automatically detected by the infrared. An ATMEGA328 series microcontroller controls the flame sensor and the whole operation. A motor driver IC, L298N, is interfaced to the microcontroller through which the controller drives the motors. As a result, the robot can detect fire from a distance. The average length for detecting flame is approximately 5.11cm, and Bluetooth transmission is about 300cm. It has the potential to reduce human error and limitations associated with fire extinguishing tasks.

A New Approach to Vision-based Fire and its Intensity Computation Using SPATIO-Temporal Features

Currently, fire detection systems based on computer vision techniques are highly appreciated for their intelligent detections at earliest. These systems use surveillance cameras to capture high-level information from a fire that enables a system to take preventive and corrective measures before the happening of a fire hazard. Handling false fire detection and reducing false alarm in such developed systems are still big challenges that need to be addressed. In this paper, a novel framework is proposed that uses angular and regional area information of the fire flame to predict the existence of a fire flame in sequence of a video frames. The proposed system especially handles false detection of fire object in video. The results achieved on different dataset of fire videos show that extracted features using the proposed framework efficiently distinguish fire and non-fire objects. These features are also useful to estimate the size and direction of a fire flame. The regional area information can be fed into a machine-learning algorithm to learn a model for a fire flame that can be used to predict about the existence of fire flame.

Analysis of Sound Pressure and Frequency Characteristics of Fire-Alarm Bells and Electronic Sirens

In the event of fire, how quickly occupants can hear, see, and/or smell the fire and then exit the building are important for reducing the number of potential casualties. After a person or an automatic fire-detection system detects a fire, an installed emergency alarm system is used to alert building occupants about the fire. The emergency alarm system plays an important role in alerting the occupants to the fire by emitting a high-pitched sound when the fire is initially detected. Although bells and electronic sirens can both be used in fire-alarm systems, usually only bells are used in most commercial fire alarms except for a few fire extinguishers. Recently, however, the development of circuit integration technology and subsequent competitive pricing and improved performance have fostered an environment favorable for the widespread application of electronic sirens. However, because electronic sirens that emit various sounds will likely confuse building occupants used to hearing familiar-sounding conventional fire-alarm bells, electronic sirens must be engineered to sound like conventional fire-alarm bells. Therefore, in this study, experiments were conducted to measure the specific sound pressure and frequency characteristics of commercially available fire-alarm bells and electronic sirens, and their characteristics were reviewed. In addition, the differences between the bells and sirens were analyzed to develop a plan for supplementing warning sounds of electronic sirens.

Attention based CNN model for fire detection and localization in real-world images

Fire is a severe natural calamity that causes significant harm to human lives and the environment. Recent works have proposed the use of computer vision for developing a cost-effective automated fire detection system. This paper presents a custom framework for detecting fire using transfer learning with state-of-the-art CNNs trained over real-world fire breakout images. The framework also uses the Grad-CAM method for the visualization and localization of fire in the images. The model also uses an attention mechanism that has significantly assisted the network in achieving better performances. It was observed through Grad-CAM results that the proposed use of attention led the model towards better localization of fire in the images. Among the plethora of models explored, the EfficientNetB0 emerged as the best-suited network choice for the problem. For the selected real-world fire image dataset, a test accuracy of 95.40% strongly supports the model's efficiency in detecting fire from the presented image samples. Also, a very high recall of 97.61 highlights that the model has negligible false negatives, suggesting the network to be reliable for fire detection.

Realization of People Density and Smoke Flow in Buildings during Fire Accidents Using Raspberry and OpenCV

Fire accidents in residential, commercial, and industrial environments are a major concern since they cause considerable infrastructure and human life damage. On other hand, the risk of fires is growing in conjunction with the growth of urban buildings. The existing techniques for detecting fire through smoke sensors are difficult in large regions. Furthermore, during fire accidents, the visibility of the evacuation path is occupied with smoke and, thus, causes challenges for people evacuating individuals from the building. To overcome this challenge, we have recommended a vision-based fire detection system. A vision-based fire detection system is implemented to identify fire events as well as to count the number people inside the building. In this study, deep neural network (DNN) models, i.e., MobileNet SSD and ResNet101, are embedded in the vision node along with the Kinect sensor in order to detect fire accidents and further count the number of people inside the building. A web application is developed and integrated with the vision node through a local server for visualizing the real-time events in the building related to the fire and people counting. Finally, a real-time experiment is performed to check the accuracy of the proposed system for smoke detection and people density.

Performance of fire hotspot detection system with sensor based on angle width and voltage difference monitoring for forest security

Fires that occur naturally in the forest can cause uncontrolled fires due to the rapid spread of heat. This research is focused on the observation land in the Puncak Besar area of Pacet in Pengalengan District, Indonesia, where the area of land burned is approximately 100 hectares. The early warning system that was built in this study uses a range widening method. This method consists of 1 sector that functions to detect heat and initial gas that occurs in the remote area. The initial area of the hotspot is usually not detected by the forest operator. After testing the sensor performance on this device, the fire sensor can detect hotspots with an average range of 440 cm. The width of the detection angle using a shield can reach a range of - 45° to 45° and the wide angle of detection of a fire without a shield can reach a range of -90° to 90°. While the communication system on this device uses the GPRS/GSM module to send data to the Android application as a monitoring system. By using this early forest fire detection system, forest operators can monitor the starting point of a fire in remote areas around the forest and minimize the spread of fire points as one solution to overcome the wider spread of forest fires.

Integrated Mobile Veld Fire Detection and Alerting System for Rural Communities

Integrated Mobile Veld Fire Detection and Alerting System for Rural Communities

An Improvement of the Fire Detection and Classification Method Using YOLOv3 for Surveillance Systems.

Currently, sensor-based systems for fire detection are widely used worldwide. Further research has shown that camera-based fire detection systems achieve much better results than sensor-based methods. In this study, we present a method for real-time high-speed fire detection using deep learning. A new special convolutional neural network was developed to detect fire regions using the existing YOLOv3 algorithm. Due to the fact that our real-time fire detector cameras were built on a Banana Pi M3 board, we adapted the YOLOv3 network to the board level. Firstly, we tested the latest versions of YOLO algorithms to select the appropriate algorithm and used it in our study for fire detection. The default versions of the YOLO approach have very low accuracy after training and testing in fire detection cases. We selected the YOLOv3 network to improve and use it for the successful detection and warning of fire disasters. By modifying the algorithm, we recorded the results of a rapid and high-precision detection of fire, during both day and night, irrespective of the shape and size. Another advantage is that the algorithm is capable of detecting fires that are 1 m long and 0.3 m wide at a distance of 50 m. Experimental results showed that the proposed method successfully detected fire candidate areas and achieved a seamless classification performance compared to other conventional fire detection frameworks.

Fire Detection System Using Android-Based Microcontroller

The Fire Detection System can be supported by Internet of Things technology, e.g. a Microcontroller device which is used to control the related devices. In this study, android-Based fire detection system was designed in which the house owner can always monitor the condition of the house all the times and accessing the information about their house when a fire occurs until the fire suppression process is complete. Information of the house condition will be displayed on the Blynk application which is located in the kitchen area and is connected to several supporting sensors. The design of a Fire Detection System Using an Android-Based Microcontroller is divided into several stages, namely: (1) Requirement Identification; (2) Requirement Analysis;(3) Hardware Design; (4) The software design (Arduino IDE 1.8.5 and Blynk). The testing results showed that the android-based Fire Detection System Using Microcontroller was able to provide information to residents of the house in the real-time.