A Simple and Real-Time Support System for Firefighters Using Low-Cost 3-DOF Accelerometer and CO Sensor

Authors

  • Dinh Nhu Dang Faculty of Fire Engineering and Technology, University of Fire Prevention and Fighting
  • Thanh Van Pham Faculty of Fire Engineering and Technology, University of Fire Prevention and Fighting
  • Tan Duc Tran Faculty of Electrical and Electronic Engineering, Phenikaa University
  • An Van Tran University of Fire Prevention and Fighting
  • An Huu Nguyen University of Fire Prevention and Fighting
  • Anh Duc Nguyen University of Fire Prevention and Fighting

DOI:

https://doi.org/10.3991/ijoe.v18i10.26425

Keywords:

Fall detection, Posture recognition, Cascade posture recognition after 3s

Abstract


During the operations, firefighters can be injured or killed because of the smoke and heat emission from the fire area, broken structure elements such as floors, walls, or boiling liquid ejection and gas explosion. Therefore, this paper aims to develop an efficient and portable system to monitor falls and high CO level through integrating a three degrees of freedom accelerometer and an MQ7 sensor to recorded acceleration and measured CO concentration with the embedded fall and high CO detection algorithms. The embedded fall detection algorithm can detect fall events with ultra-high accuracy without mistakenly identifying normal activities such as walking, standing, jogging, and jumping as fall events. The posture recognition and cascade posture recognition after three seconds are proposed in this paper to gain the accuracy of our proposed fall detection system. If a firefighter falls and is unable to stand up, the alert signal message will be sent to their commander outside through the GSM/GPRS module. The embedded high CO detection algorithm used to alert the dangerous CO level to recommend using self-contained breathing apparatuses (SCBA) and saving fresh air with acceptable CO level. We carefully investigated the proposed thresholds and window size before embedding them into the microcontroller. The sensitivity and accuracy achieved were around 96.5% and 93% respectively in our recorded data. Furthermore, the proposed fall detection algorithm also achieved higher geometric mean in comparison with Support Vector Machine classifier (SVM) and a nearest neighbor rule (NN) in the public datasets with the achieved around 99.44%, 98.41% and 95.76% respectively.

Author Biographies

Dinh Nhu Dang, Faculty of Fire Engineering and Technology, University of Fire Prevention and Fighting

Dang Nhu Dinh was born in 1980. He received his B.Sc, M.Sc and PhD degrees respectively in 2009, 2011, 2017 at Hanoi University of Science Technology (HUST), Vietnam. He is currently a lecturer in the Department of Fire protection systems,  Faculty of Fire Engineering and Technology, University of Fire Prevention and  Fighting  (UFPF). He is the author and co-author of 19 papers on fire protection engineering, antenna and wireless communications.

Thanh Van Pham, Faculty of Fire Engineering and Technology, University of Fire Prevention and Fighting

Pham Van Thanh was born in 1990. He received the M.Sc. degree in Electronics and Telecommunication at University of Engineering and Technology (UET) in 2012. He is currently a lecturer in the Department of Fire protection systems, Faculty of Fire Engineering and Technology, University of Fire Prevention and Fighting (UFPF).  His research areas of interest include: Signal and Image Processing, Personal Safety Equipment, Firefighter Supporting Devices and Fire Protection Systems.

Tan Duc Tran, Faculty of Electrical and Electronic Engineering, Phenikaa University

Tan D. Tran is an Associate professor and Vice Dean of Faculty of Electrical and Electronic Engineering (FEEE), Phenikaa University. From August 2015 to May 2019, he was an Associate professor and Vice Dean of Electronics and Telecommunication Faculty, VNU University of Engineering and Technology. He has published over 150 research papers. His main research interests include the representation, processing, analysis, and communication of information embedded in signals and datasets. He serves as a TPC co-chair, a technical committee program member, track chair, session chair and reviewer of many international conferences and journals.

An Van Tran, University of Fire Prevention and Fighting

An-Van Tran was born in 1979. He obtained M.A degree from University of Languages and International Studies – Vietnam National University, Hanoi. He is currently a teacher of ESP at University of Fire Fighting and Prevention in Hanoi. His interest is translation of technical materials from English into Vietnamese, especially English for fire profession and research in the field of linguistics. He has had several articles published on Journal of Fire - University of Fire Prevention and Fighting.

An Huu Nguyen, University of Fire Prevention and Fighting

Nguyen Huu An was born in 1991. He received his degree of engineer in Fire prevention and fighting in 2014 at University of Fire Fighting and Prevention. Since 2014, he is  currently  a  lecturer  in  the  Department  of  Fire  protection  systems,  Faculty of Fire Engineering and Technology, University of Fire Prevention and  Fighting (UFPF). His main research interests are: Fire Protection Systems, mobile robotics, localization of mobile robots. Currently, he has been published several papers on fire safely journal.

Anh Duc Nguyen, University of Fire Prevention and Fighting

Nguyen Duc Anh was born in 1977. He received his Bachelor and Master degrees at Le Quy Don University respectively in 2008, 2010 and PhD. degrees at Academy of Military Science and Technology in 2016. He is the author and co-author of more than 20 papers on fire protection engineering, digital signal processing and automation.
Covr iJOE Vol. 18 No. 10 (2022)

Downloads

Published

2022-07-26

How to Cite

Dang, D. N., Pham, T. V., Tran, T. D., Tran, A. V., Nguyen, A. H., & Nguyen, A. D. (2022). A Simple and Real-Time Support System for Firefighters Using Low-Cost 3-DOF Accelerometer and CO Sensor. International Journal of Online and Biomedical Engineering (iJOE), 18(10), pp. 4–25. https://doi.org/10.3991/ijoe.v18i10.26425

Issue

Vol. 18 No. 10 (2022)

Section

Papers

License

Copyright (c) 2022 Dinh Nhu Dang, Thanh Van Pham, Tan Duc Tran, An Van Tran, An Huu Nguyen, Anh Duc Nguyen

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.