Fire Safety and Alerting System in Railways

Devan, P. Arun Mozhi; Gahlot, Manisha; Rajarajeswari, K.G.T.; Priyanga, M.; Sangeetha, K.

doi:10.1109/rteict42901.2018.9012364

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…Samit Kumar Ghosh ,P B Natarajan , Sankata Bhanjan Prusty,"Intelligent Smart Home Automation System based on LabVIEW" [6] design for home automation with some intelligent functionalities. The system is based on the LabVIEW and can act as a security guard of the home.…”

Section: Literature Reviewmentioning

confidence: 99%

Automatic Fire Suppression of Home Automation System Using Graphic System Design

et al. 2023

Preprint

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This project involves the development of Fire Suppression System (FSS) leveraging of Home automation system using Graphical System design (LabVIEW) software and Arduino microcontroller for real-time monitoring and control. The system integrates an Infrared (IR) flame sensor, an MQ2 gas sensor to detect and suppress fire hazards efficiently. The LabVIEW interface facilitates real-time monitoring of sensor data, allowing users to visualize and analyze the environmental conditions. Through this system, fires are automatically subdued, enhancing safety without requiring human intervention. This advances fire safety by swiftly containing threats and minimizing potential damage.

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Section: Literature Reviewmentioning

confidence: 99%

Automatic Fire Suppression of Home Automation System Using Graphic System Design

et al. 2023

Preprint

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“…The proposed method provides GSM (Global System for Mobile communication) along with gas/smoke sensors integrated with LM35 to prevent the fire accidents. The Arduino enables the buzzer and gives the alert signal to GSM network, If the temperature is greater than 80 then motor will rotate and open the knob of the fire extinguisher when the heat sensor senses the temperature, thus preventing fire [5]. To fault is identified and fault location is also determined with the help of proposed design of IR (Infrared Radiation) sensor and GPS (Global Positioning System) with the control of longitude and latitude coordinates which is sent to predefine a mobile number [6].…”

Section: ░ 2 Principlesmentioning

confidence: 99%

Demonstration of an Intelligent and Efficient Smart Monitoring System for Train Track By using Arduino

Roy,

Rajalakshmi,

Sangeetha

2023

IJEER

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In Indian railway, the smart monitoring system for the train also train track is a significant aspect to prevent accidents. Indian railway system is underdeveloped in terms of smart monitoring of the train when compared with the other developed countries. Using the smart monitoring system for train, the deterioration of the railway track could be identified and secondly, accident between two trains could be prevented, thirdly any obstacle present in railway track, could be find and removed, two coaches of the train getting disconnected during the movement of the train due to manufacturing mistakes could also be detected. It helps to detect fire in the particular coach of train. Smart monitoring of the train can be achieved by the help of some semiconductor devices such as laser, laser camera and photodiode is used. Smart monitoring system of the railway could help to monitor the train and its track in an efficient way it could be implemented in Indian railway to avoid accident and extricate people’s life.

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“…Thus, the aim of indoor fire perception is capturing corresponding changes quickly and accurately, and then responding. Sensor-based fire detectors have been widely used in various fields of fire detection, owing to convenient installation and real-time monitoring [3][4][5][6]. Fire detection technology has developed rapidly over the past 100 years since the first temperature-sensitive fire detector was designed and implemented in 1890 in the UK [7].…”

Section: Introductionmentioning

confidence: 99%

Research on Multi-Sensor Fusion Indoor Fire Perception Algorithm Based on Improved TCN

Zeng

et al. 2022

Sensors

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Indoor fires cause huge casualties and economic losses worldwide. Thus, it is critical to quickly and accurately perceive the fire. In this work, an indoor fire perception algorithm based on multi-sensor fusion was proposed. Firstly, the sensor data features were fully extracted by improved temporal convolutional network (TCN). Then, the dimension of the extracted features was reduced by adaptive average pooling (AAP). Finally, the fire classification was realized by the support vector machine (SVM) classifier. Experimental results demonstrated that the proposed algorithm can improve accuracy of fire classification by more than 2.5% and detection speed by more than 15%, compared with TCN, back propagation (BP) neural network and long short-term memory (LSTM). In conclusion, the proposed algorithm can perceive the fire quickly and accurately, which is of great significance to improve the performance of the current fire prediction systems.

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Fire Safety and Alerting System in Railways

Cited by 6 publications

References 8 publications

Automatic Fire Suppression of Home Automation System Using Graphic System Design

Automatic Fire Suppression of Home Automation System Using Graphic System Design

Demonstration of an Intelligent and Efficient Smart Monitoring System for Train Track By using Arduino

Research on Multi-Sensor Fusion Indoor Fire Perception Algorithm Based on Improved TCN

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