텍스트 마이닝 기법을 이용한 기후변화 적응 분야 특허 분석: 수재해 대응을 중심으로

To analyze the trends of climate change adaptation technologies, this study analyzed patent data focusing on the field of water disaster response using the Latent Dirichlet Allocation model, one of the text mining techniques. The technologies for responding to climate change-induced water disasters were classified based on the Climate Technology Classification : water systems and aquatic ecosystems, water disaster management, climate forecasting and modeling, and climate information warning systems. As a result of the analysis, in the water system and aquatic ecosystems sector, data modeling technologies for river water quality and pollution assessment are prominent, and technologies such as flood control structures and devices are also increasing in importance. In the field of water disaster management, technologies for automatic control of floodgates and embankment reinforcement for flood prevention were prominent, and the construction of intelligent river disaster management systems utilizing the Internet of Things was on the rise. In the field of climate forecasting and modeling, there has been a focus on weather and climate air quality prediction technologies and air quality measurement devices, and demand for mobile air pollution measurement equipment is also increasing. Finally, in the field of climate information warning systems, flood prediction models based on precipitation data and water level management and predictive warning models were identified as key technologies, and there is growing interest in improving the accuracy of prediction models using artificial intelligence. This study provides important implications for the establishment of technology strategies to respond to climate change, and is expected to provide useful information for future research on climate change adaptation technologies.