Klaus Schwab, who is the founder and executive chairman of the World Economic Forum, published a book "The Fourth Industrial Revolution" in January 2016 and this word was spread to the world since then. The fourth industrial revolution began in the early 2010s and various X-Tech businesses such as AgriTech, EdTech, FinTech, HealthTech, HRTech, etc. have been growing. The author had been deeply involved in growing HRTech and EdTech businesses in Japan through industry-academia-government collaboration and the breakthrough structure in X-Tech businesses was clarified through the case studies of HRTech and EdTech businesses. Since X-Tech businesses were cross-industry new businesses and mostly public policy dependent, it was clarified that strategic PR (Public Relations) and GR (Government Relations) were important to develop new markets. And the approaches to grow the markets and businesses through strategic PR and GR were structured.

This study aims to evaluate the performance of various large language models (LLMs) in generating dengue fever epidemic and earthquake intensity maps through the integration of spatial information technology. By combining natural language processing techniques, this paper presents an innovative method to extract real-time data related to dengue fever and earthquake events, which is then used to generate corresponding geographic information maps, thereby improving real-time monitoring and disaster management efficiency. The research designed a series of detailed prompts, including topic descriptions, data sources, analysis objectives, and specific requirements, to test the capabilities of multiple LLMs in the code generation process. The codes generated by these models were further used to map the geographic distribution of dengue fever outbreaks and earthquake intensities in Taiwan. Subsequently, the codes were evaluated on accuracy, operational efficiency, and the clarity of the visualized results. The findings revealed that in addition to ChatGPT, models such as Copilot, Claude, and Nxcode-CQ-7B-orpo also excelled at generating precise and efficient maps. These LLMs are capable of automating the processing of large amounts of data and generating visualized charts with decision support functions, significantly reducing the time and labor costs associated with traditional manual operations. In addition, this innovative approach provides a new technical pathway for real-time geographic disaster monitoring and management. The results underscore the value of integrating LLMs with spatial information technology, offering new research directions for geographic information systems applications and providing robust technical support for disaster response and public health management.