Weqaa: An Intelligent Mobile Application for Real-Time Inspection of Fire Safety Equipment

Authors

  • Rehab Alidrisi College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia
  • Ekram Feras College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia
  • Shahad Aboukozzana College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia
  • Alaa Alomayri College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia
  • Asmaa Alayed College of Computing, Umm Al-Qura University, Makkah, Saudi Arabia
Volume: 14 | Issue: 3 | Pages: 14088-14095 | June 2024 | https://doi.org/10.48084/etasr.7229

Abstract

Fire safety is an important consideration, particularly in buildings where there are significant risks linked to a possible fire breakout. Therefore, it is crucial to implement procedures and regulations in buildings to minimize fire damage. Despite the installation of various pieces of Fire Safety Equipment (FSE), over time their effectiveness may be reduced due to factors, such as failure, damage, and insufficient maintenance. For this reason, the fire safety inspection process came to ensure the FSE availability and efficiency. Visual fire safety inspection conducted by civil defense is found to be time-consuming and inefficient, primarily due to manual procedures and difficulty in identifying defects, leading to inaccurate results and low performance. The purpose of this research is to enhance and automate fire safety inspection by implementing deep learning and computer vision techniques in a mobile application, thus addressing the challenges associated with visual inspection. Weqaa application allows the inspector to point their mobile phone camera at the fire extinguisher, then determine the condition of the extinguisher, document it, and report it to the relevant authority to quickly determine the appropriate action procedure. Interviews with expert inspectors were performed to outline the required functions of the application. The mobile application was developed using Flutter and being integrated with the detection model to permit the user to inspect fire extinguishers. Initial testing of the application has exhibited promising results, with inspectors noting its competence in detecting violations and improving inspection processes. The use of the particular application enabled the inspectors to perform the required functions faster, more accurately, and with fewer errors compared to the visual inspection deployment, indicating the application's effectiveness in detecting violations.

Keywords:

fire safety inspection, Fire Safety Equipment (FSE), mobile application, visual inspection, deep learning, computer vision

Downloads

Download data is not yet available.

References

D. Rasbash, G. Ramachandran, B. Kandola, J. Watts, and M. Law, Evaluation of Fire Safety, 1st ed. Hoboken, N.J, USA: Wiley, 2004.

"Annual Statistical Report," Civil Defense Directorate, Saudi Arabia, 2020.

D. E. Della-Giustina, Fire Safety Management Handbook, 3rd ed. Boca Raton, FL, USA: CRC Press, 2014.

"New survey highlights the importance of fire extinguishers," SecurityWorldMarket.com, Jun. 19, 2022. https://www.securityworldmarket.com/me/News/Business-News/survey-finds-93-of-fires-put-out-with-portable-extinguishers.

D. Dieken, "Inspection, testing and maintenance of fire protection systems at industrial plants," Process Safety Progress, vol. 18, no. 3, pp. 151–155, 1999.

Saudi Building Code National Committee, Saudi Fire Protection Code SBC 801 - CR. Saudi Arabia, 2018.

"Statement on JGH Fire Investigations," Ministry of Health in Saudi Arabia. https://www.moh.gov.sa/Ministry/MediaCenter/News/Pages/News-2016-01-13-001.aspx.

"Questionnaire about the Process of FSE Inspection," Google Docs. https://forms.gle/FfwETkfbhc5DxGJ18

R. S. T. Lee, Artificial Intelligence in Daily Life. Springer, 2020.

F. M. U. Baran, L. S. A. Alzughaybi, M. A. S. Bajafar, M. N. M. Alsaedi, T. F. H. Serdar, and O. M. N. Mirza, "Etiqa’a: An Android Mobile Application for Monitoring Teen’s Private Messages on WhatsApp to Detect Harmful/Inappropriate Words in Arabic using Machine Learning," Engineering, Technology & Applied Science Research, vol. 13, no. 6, pp. 12012–12019, Dec. 2023.

L. Loyani and D. Machuve, "A Deep Learning-based Mobile Application for Segmenting Tuta Absoluta’s Damage on Tomato Plants," Engineering, Technology & Applied Science Research, vol. 11, no. 5, pp. 7730–7737, Oct. 2021.

"Madani Application." Saudi Civil Defense, [Online]. Available: https://apps.apple.com/sa/app%D9%85%D8%AF%D9%86%D9%8A/id1596908770.

"Salamti Application." Saudi Civil Defense, [Online]. Available: https://my.998.gov.sa/app/salamati.

I. Sommerville, Software Engineering, 9th ed. Boston, MA, USA: Pearson, 2011.

"Firebase | Google’s Mobile and Web App Development Platform." Google, [Online]. Available: https://firebase.google.com/.

"Flutter - Build apps for any screen." Google, [Online]. Available: https://flutter.dev/.

"Google Maps Platform." Google, [Online]. Available: https://developers.google.com/maps.

A. Alayed, R. Alidrisi, E. Feras, S. Aboukozzana, and A. Alomayri, "Real-Time Inspection of Fire Safety Equipment using Computer Vision and Deep Learning," Engineering, Technology & Applied Science Research, vol. 14, no. 2, pp. 13290–13298, Apr. 2024.

"Welcome to Flask — Flask Documentation (3.0.x)," Flask. https://flask.palletsprojects.com/en/3.0.x/.

H. Sharp, J. Preece, and Y. Rogers, Interaction Design: Beyond Human-Computer Interaction, 6th ed. Indianapolis, IN, USA: Wiley, 2023.

Downloads

How to Cite

[1]
R. Alidrisi, E. Feras, S. Aboukozzana, A. Alomayri, and A. Alayed, “Weqaa: An Intelligent Mobile Application for Real-Time Inspection of Fire Safety Equipment”, Eng. Technol. Appl. Sci. Res., vol. 14, no. 3, pp. 14088–14095, Jun. 2024.

Metrics

Abstract Views: 275
PDF Downloads: 150

Metrics Information

Most read articles by the same author(s)