Design of fire Design of Fire Detection System Based on Artificial Intelligence Technology

In this era of rapid development of network and technology, data has become the most important part of companies and people. In fact, the software and system series are just the framework for storing data, and real data occupies an important position in the entire communication. This paper focuses on data mining and management models of public data resources. Starting from how to mine useful information from public data resources and how to manage such data, it puts forward several classifications of big data management models and their respective advantages.

Digital Print Synthesis Based on Image Processing and Interactive Technology

Fire is a common disaster, which causes major threats and losses to human life and property. Countries around the world have been committed to the study of the mechanism and internal mechanism of fires, with the goal of preventing fires from occurring and minimizing the losses caused by fires. Among the many methods, fire detection technology is an effective method to prevent and reduce the occurrence of fire. This article focuses on the research of the fire detection system based on artificial intelligence technology, improves the accuracy of the fire detection system by introducing artificial intelligence technology into the fire detection system, and uses experiments to verify the error rate of the artificial intelligence technology fire detection system. The experimental results show that the system’s detection of fire is not very different from the actual situation, and the error rate is within 10%. Then compared with the traditional detection system, the detection performance is relatively high, and the error rate can be reduced by one time.

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.

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.

Dual Operated Firefighting Robot

In this study, a dual operated firefighting robot was designed, fabricated and analyzed. The robot can be operated in both RC and automatic modes. The robot consists of three different types of system units- fire detection system, extinguishing system and communication system. The fire detection system uses flame sensors for detection of fire. The extinguishing unit consists of fire extinguisher cylinder mounted on the robot which can be controlled by the user through a remote. . The fire extinguisher is operated with the help of a relay circuit. The whole set up is controlled and monitored by the main controller or microprocessor. Using a belt drive enables the robot to climb stairs. The main chassis consists of 400mm*390mm aluminum profile. Four motors, each of 60 rpm, are used which provides adequate thrust for motion. The power supply for the functioning of robot is provided by a 12V, 7 AH battery. The compact design of the firefighting robot enables it to enter small or narrow space with ease. More over the dual operation ability of the robot helps to increase the overall efficiency of the robot.