Development of IoT-based automated dynamic emergency response system against fire incidents in academic building

• Main Authors: Al-Hady, Syed Mohammed Zakaria, Islam, Md Rafiqul, Rashid, Muhammad Mahbubur
• Format: Article
• Language: English
• Published: Deer Hill Publications 2023
• Subjects: TK9001 Nuclear engineering. Atomic power
• Online Access: http://irep.iium.edu.my/109563/7/109563_Development%20of%20IoT-based%20automated%20dynamic%20emergency%20response.pdf; http://irep.iium.edu.my/109563/; https://www.deerhillpublishing.com/index.php/ijemm/issue/view/33; https://doi.org/10.26776/ijemm.08.03.2023.03

The ongoing advancement of architectural and structural designs, high-ceiling spaces, special spaces have made fire disasters increasingly diverse and difficult to predict. It is demanding the need for improved firefighting systems. This study aims to address the need for improved firefighting systems in academic building by proposing the development of an IoT-based automated emergency response website. The proposed system leverages IoT technology, wireless and bluetooth sensor networks to gather real-time data from various sensors and devices installed in the site and uses machine learning algorithms to predict and prevent potential fire incidents. The system also includes an emergency response website that allows users to access real-time information about the fire incident, location, severity, and evacuation instructions. Additionally, the proposed system incorporates Building Information Modelling (BIM) to optimize evacuation and rescue routes, providing early detection and accurate alarm capabilities, evacuation guidance for endangered individuals, and guidance for firefighters. The integration of BIM allows the system to provide a three-dimensional visualization of the site, enabling a more efficient and effective response to fire incidents. Overall, the proposed system aims to improve the safety and security through real-time monitoring and response capabilities. By leveraging the power of IoT technology, machine learning algorithms and BIM, the proposed system aims to reduce the impact of fire disasters by providing accurate and timely information, route optimization and facilitating effective evacuation and rescue efforts. Keywords: Building Information Model