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.

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Model Pendeteksi Api dalam Ruangan Berbasis SMS Menggunakan Logika Fuzzy

JISA(Jurnal Informatika dan Sains) ◽

10.31326/jisa.v2i2.498 ◽

2019 ◽

Vol 2 (2) ◽

Author(s):

Deden Ardiansyah ◽

Anjyaz Anjani

Keyword(s):

Fuzzy Logic ◽

Detection System ◽

Human Life ◽

Control Unit ◽

Fire Detection ◽

Automation System ◽

Security Level ◽

Fire Hazards ◽

Fire Detection System ◽

Arduino Uno

Automation system in its function to helps and makes human life easier has experienced a significant growth in recent years, for example in security field. Low security level such as no fire detection system is one of the factors which is supporting the possibilities of fire accidents to happen. This system detects the possibilities fire using fuzzy logic. This system uses microcontroller Arduino Uno as control unit, flame sensor to check infrared ray from the fire, DHT11 temperature sensor to monitor the temperature in the room, and GSM shield to send SMS. Sensors will detect fire in the room and send the collected information to be processed by Arduino Uno by implementing fuzzy logic. SMS-Based Indoor Fire Detection System Models Using Fuzzy Logic has many benefits in the development of room safety systems from fire hazards. The design of this system is simple but can be widely applied to further research development.

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IoT based forest fire detection system

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.7.10277 ◽

2018 ◽

Vol 7 (2.7) ◽

pp. 124 ◽

Cited By ~ 5

Author(s):

M Trinath Basu ◽

Ragipati Karthik ◽

J Mahitha ◽

V Lokesh Reddy

Keyword(s):

Forest Fire ◽

Temperature Sensor ◽

Room Temperature ◽

Detection System ◽

Fire Detection ◽

Family Unit ◽

The Status ◽

Fire Detection System ◽

Smoke Sensor ◽

Forest Fire Detection

It has been found in a survey that 80% losses caused due to fire would have been kept away from if the fire was identified promptly. Node Mcu based IoT empowered fire indicator and observing framework is the answer for this issue.In this task, we have assembled fire finder utilizing Node Mcu which is interfaced with a temperature sensor, a smoke sensor and signal. The temperature sensor detects the warmth and smoke senssor detects any smoke produced because of consuming or fire. buzzer associated with Arduino gives us an alert sign. At whatever point fire activated, it consumes protests adjacent and produces smoke. A fire caution can likewise be activated because of little smoke from candlelight or oil lights utilized as a part of a family. Likewise, at whatever point warm force is high then additionally the alert goes on. Bell or alert is killed at whatever point the temperature goes to ordinary room temperature and smoke level decreases. We have additionally interfaced LCD show to the Node Mcu board.With the assistance of IoT innovation.Node MCU fire checking serves for mechanical need and also for family unit reason. At whatever point it recognizes fire or smoke then it immediately alarms the client about the fire through the ethernet module. For this reason, we are utilizing ESP8266 which is from Arduino IDE. Likewise, the Node Mcu interfacing with LCD show is done to show the status of the framework whether the Smoke and Overheat is identified or not. What's more, Node Mcu interfacing with Ethernet module is done as such that client become more acquainted with about the predominant condition message. It insinuate the client about the fire identification. This framework is extremely helpful at whatever point the client isn't in the closeness of control focus. At whatever point a fire happens, the framework naturally faculties and alarms the client by sending an alarm to an application introduced on user’s Android portable or page open through web.

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Digital Print Synthesis Based on Image Processing and Interactive Technology

Journal of Physics Conference Series ◽

10.1088/1742-6596/2146/1/012028 ◽

2022 ◽

Vol 2146 (1) ◽

pp. 012028

Author(s):

Lijun Sun

Keyword(s):

Artificial Intelligence ◽

Error Rate ◽

Detection System ◽

Human Life ◽

Fire Detection ◽

Detection Technology ◽

Artificial Intelligence Technology ◽

Internal Mechanism ◽

Fire Detection System ◽

The Many

Abstract 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.

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

Sustainability ◽

10.3390/su131911082 ◽

2021 ◽

Vol 13 (19) ◽

pp. 11082

Author(s):

Gajanand S. Birajdar ◽

Mohammed Baz ◽

Rajesh Singh ◽

Mamoon Rashid ◽

Anita Gehlot ◽

...

Keyword(s):

Real Time ◽

Web Application ◽

Detection System ◽

Human Life ◽

Fire Detection ◽

Smoke Detection ◽

Urban Buildings ◽

System A ◽

Fire Detection System ◽

Fire Accidents

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.

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