Weqaa: An Intelligent Mobile Application for Real-Time Inspection of Fire Safety Equipment
Received: 11 March 2024 | Revised: 24 March 2024 and 27 March 2024 | Accepted: 30 March 2024 | Online: 8 April 2024
Corresponding author: Asmaa Alayed
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 visionDownloads
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Copyright (c) 2024 Rehab Alidrisi, Ekram Feras, Shahad Aboukozzana, Alaa Alomayri, Asmaa Alayed
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