Integrating Bluetooth-Enabled Sensors with Cloud Computing for Fire Hazard Communication Systems

Abstract

Due to the complex modern construction processes and the diversity of building materials, a diversified construction environment has emerged, making it difficult to accurately predict and monitor the risk of fire hazards. Therefore, the development and implementation of a fire hazard detection system are necessary to effectively prevent fires at the source and to adequately protect construction personnel and building assets. On construction sites, early warning for fires often occurs after the fire has occurred, resulting in missing the best time for fire rescue. However, building information modeling (BIM) and wireless sensor networks have been widely discussed in many aspects of building disaster prevention management as methods for fire detection and early warning. In this study, a fire hazard intelligent detection system is constructed using a cloud computing platform and Bluetooth sensors. The system uses embedded Bluetooth wireless sensors to form a topology, and the cloud computing platform and user interface are written based on Python to create a two-way fire hazard detection system that displays real-time and dynamic detection information. The results based on practical case applications show that the cloud computing platform processed can effectively provide monitoring information to support fire safety assessment and planning, early detection and alarm response, guide effective decision-making, and facilitate fire rescue and control efforts to improve overall building safety and disaster response capabilities.