Mapping the Knowledge Structure and Evolutionary Trends in Fire Detection Technologies: A CiteSpace-Based Visual Analysis

This study provides a comprehensive review of the current research status of fire detection technologies. Based on the data from the Web of Science Core Collection database, using the CiteSpace software, a visual analysis was conducted on the research hotspots, collaboration networks, and evolution trends of fire detection technologies from 2005 to 2024. The results show that: 1) The number of published documents has generally shown an upward trend; 2) There has been a certain number of network-like cooperative structures formed among various institutions and authors, among which Chinese research institutions constitute the main hub. The internal cooperation within the cooperative clusters is quite evident, but cross-cluster and cross-national regional cooperation still needs to be strengthened; 3) The development and evolution of research methods can be mainly divided into three main stages. Currently, research methods are gradually moving towards the integration of intelligent algorithms and experimental research, the collaborative innovation between big data models and statistical surveys, and the widespread application of comprehensive optimization technologies based on artificial intelligence. 4)The deep integration and application of emerging technologies such as deep learning algorithms, Internet of Things (IoT), and artificial intelligence in fire detection technology have become the research frontier in this field. However, in the future, the maturity and potential flaws of the integrated application of these emerging technologies still require further study. This study provides researchers with a systematic overview of current research gaps and emerging hotspots in global fire detection technology, while identifying potential directions for future research. Furthermore, this research holds significant engineering value for fire prevention and fire safety protection in scenarios such as buildings and forests.