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The primary objective of the current fire protection system in high-rise buildings is to extinguish fires in close proximity to the detectors. However, in the event of rapidly spreading fires, it is more effective to limit the transmission of fire and smoke. This study aims to develop an IoT-based real-time pre-response system for high-rise building fires that is capable of limiting the spread of fire and smoke. The proposed system collects fire data from sensors and transmits them to a cloud computer for real-time analysis. Based on the analysis results, the cloud computer controls the actions of alarm devices, ventilation equipment, and fine water mist nozzles. The system can dynamically adjust the entire system's behavior in real time by adopting pre-response measures to extinguish fires and limit the spread of fires and smoke. The system was tested on a simulation platform similar to actual high-rise buildings to evaluate its impact on fires and smoke. The results demonstrate the system's effectiveness in extinguishing fires and suppressing the spread of fires and smoke. [ABSTRACT FROM AUTHOR]

To satisfy the demand for rapid prediction of smoke transmission paths in high-rise building fires, a graph-based model was developed. The model represents a high-rise building as a Directed Acyclic Graph (DAG) grid model and employs computer simulation to determine the smoke transmission path and generate prediction results. The results were compared with those from similar simulations and were found to be consistent, indicating the feasibility and objective nature of the prediction results. Compared to other methods, this model has a shorter modeling time and can quickly provide prediction results. Furthermore, it can be applied to buildings of any structure, thus serving as a reference for smoke control design in high-rise building fire protection systems, particularly in cases involving complex internal structures. [ABSTRACT FROM AUTHOR]