Comparative Analysis of Real Fires for Electric Vehicles and Gasoline Vehicles

Recently, the demand for electric vehicles has increased rapidly as eco-friendly vehicles to regulate exhaust gas emissions. However, fire accidents related to electric vehicles are also occurring frequently. In the present work, to design a fire suppression plan for electric vehicles, a comparison of electric and gasoline vehicles has been demonstrated through real fire experiments. Temperature measurements have been performed using a heat flux sensor to understand the characteristics of each fire. At the peak of fire, the maximum temperature was measured to be about 1,390 ℃ or higher. Further, it was confirmed that gasoline vehicles exhibit higher temperature gains than electric vehicles.

A Study on Strengthening Standards for Fire Prevention of Anti-freeze Electric Heating Cable

As per the fire statistics survey of 2019, 56.5% (152 cases) of the entire fire accidents (269 cases) caused by heating cables were due to electrical factors. Therefore, in the present work, the electrical factors responsible for heating cable fire have been analyzed, and fire prevention measures have been demonstrated through related reproduction experiments. According to heating cable fire statistics, the fire in anti-freezing appliances (heating cables), except for fires caused by electric cable arcing and other unknown factors, can be classified into four types based on installation configurations. These configurations have been classified and tested according to the Technical Regulations for Electrical and Telecommunications Products and Components (K 10013). The results of a comparative experiment on anti-freezing appliances (heating cable) revealed that the configuration “a type of water pipe with a heating cable wrapped around the water pipe and insulation on the outside” showed the highest temperature among the four installation arrangements. Additionally, the maximum difference between the test temperature (K 10013) and the actual temperature was 40 ℃.

Fire Detection Method in Smart City Environments Using a Deep-Learning-Based Approach

In the construction of new smart cities, traditional fire-detection systems can be replaced with vision-based systems to establish fire safety in society using emerging technologies, such as digital cameras, computer vision, artificial intelligence, and deep learning. In this study, we developed a fire detector that accurately detects even small sparks and sounds an alarm within 8 s of a fire outbreak. A novel convolutional neural network was developed to detect fire regions using an enhanced You Only Look Once (YOLO) v4network. Based on the improved YOLOv4 algorithm, we adapted the network to operate on the Banana Pi M3 board using only three layers. Initially, we examined the originalYOLOv4 approach to determine the accuracy of predictions of candidate fire regions. However, the anticipated results were not observed after several experiments involving this approach to detect fire accidents. We improved the traditional YOLOv4 network by increasing the size of the training dataset based on data augmentation techniques for the real-time monitoring of fire disasters. By modifying the network structure through automatic color augmentation, reducing parameters, etc., the proposed method successfully detected and notified the incidence of disastrous fires with a high speed and accuracy in different weather environments—sunny or cloudy, day or night. Experimental results revealed that the proposed method can be used successfully for the protection of smart cities and in monitoring fires in urban areas. Finally, we compared the performance of our method with that of recently reported fire-detection approaches employing widely used performance matrices to test the fire classification results achieved.

GSM Based SMS Alert Fire Alarm System

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

Analysis of Fire Accident Factors on Construction Sites Using Web Crawling and Deep Learning Approach

Fire safety on construction sites has been rarely studied because fire accidents have a lower occurrence compared to construction’s “Fatal Four”. Despite the lower occurrence, construction fire accidents tend to have a larger severity of impact. This study aims at using news media data and big data analysis techniques to identify patterns and factors related to fire accidents on construction sites. News reports on various construction accidents covered by news media were first collected through web crawling. Then, the authors identified the level of media exposure for various keywords related to construction accidents and analyzed the similarities between them. The results show that the level of media exposure for fire accidents on construction sites is much higher than for fall accidents, which suggests that fire accidents may have a greater impact on the surroundings than other accidents. It was found that the main causes of fire accidents on construction sites are violations of fire safety regulations and the absence of inspections, which could be sufficiently prevented. This study contributes to the body of knowledge by exploring factors related to fire safety on construction sites and their interrelationships as well as providing evidence that the fire type should be emphasized in safety-related regulations and codes on construction sites.

Motion Control System Design for a Flying-Type Firefighting System with Water Jet Actuators

This paper presents the design and modeling of a flying-type fire extinguishing system. Fire accidents present very hazardous environments, and firefighters are in danger of losing their lives while putting out the fire. Strict safety measures should be considered to guarantee safe working conditions for firefighters, which is not the case every time, as fatalities and casualties are still being recorded. For this reason, a novel fire extinguishing system is proposed to provide more safe firefighting and survivor searches. The system studied in this paper is a pilot model that consists of a water jet-based actuation system to control the flying motion of the robot. The dynamic model of this flying robot is derived using the actuation forces, water jet system characteristics, and related information. The mathematical system model is detailed, a sliding-mode control system and a proportional-integral-derivative controller are designed, and comparative simulation tests are carried out.

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.

Iot Based Smart Switch Board Technology For Smart Home

To overcome the limitations of the traditional switch board, a new system equipped with latest technologies has been developed as Smart Switch Board and which is the smarter version compared to traditional Switch Boards. An IOT based switching device has been developed and which to be controlled via Blynk application. This smart device is very useful for handicapped persons. The smart switch meter has been used to control the smaller areas if it is connected through the router. It makes the system more secured as it is working through router’s IP address. Physical contact is not required to operate; it ensures reliability and safety from fire accidents. The Hardware component are quite cheap and easy to replace.