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Wireless Communications and Mobile Computing
Volume 2018 (2018), Article ID 8235127, 11 pages
Research Article

Intelligent Smoke Alarm System with Wireless Sensor Network Using ZigBee

1Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
2School of Computer Science, Chengdu University of Information Technology, Chengdu, China
3Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
4The Chinese University of Hong Kong, Shatin, Hong Kong

Correspondence should be addressed to Shin-Ming Cheng; wt.ude.tsutn.liam@gnehcms and Jun Cheng;

Received 24 September 2017; Revised 28 December 2017; Accepted 17 January 2018; Published 22 March 2018

Academic Editor: Kun Bai

Copyright © 2018 Qin Wu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.