JOURNAL ARTICLE

Intelligent Smoke Alarm System with Wireless Sensor Network Using ZigBee

Abstract

The conflagration of fire is still a serious problem caused by humans, and houses are at a high risk of fire. Recently, people have used smoke alarms which only have one sensor to detect fire. Smoke is emitted in several forms in daily life. A single sensor is not a reliable way to detect fire. With the rapid advancement in Internet technology, people can monitor their houses remotely to determine the current condition of the house. This paper introduces an intelligent smoke alarm system that uses ZigBee transmission technology to build a wireless network, uses random forest to identify smoke, and uses E‐charts for data visualization. By combining the real‐time dynamic changes of various environmental factors, compared to the traditional smoke alarm, the accuracy and controllability of the fire warning are increased, and the visualization of the data enables users to monitor the room environment more intuitively. The proposed system consists of a smoke detection module, a wireless communication module, and intelligent identification and data visualization module. At present, the collected environmental data can be classified into four statuses, that is, normal air, water mist, kitchen cooking, and fire smoke. Reducing the frequency of miscalculations also means improving the safety of the person and property of the user.

Keywords:
Computer science ALARM Wireless sensor network Computer network Wireless Smoke NeuRFon Embedded system Real-time computing Wireless network Telecommunications Key distribution in wireless sensor networks Electrical engineering

Metrics

36
Cited By
4.59
FWCI (Field Weighted Citation Impact)
24
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Fire Detection and Safety Systems
Physical Sciences →  Engineering →  Safety, Risk, Reliability and Quality
IoT-based Smart Home Systems
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Video Surveillance and Tracking Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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