A Data Driven Approach to Measure Evolution Trends of City Information Modeling

Abstract

This work aims to reveal the current status of the city information modeling (CIM) from massive patent data, using the latent Dirichlet allocation (LDA) model, and quantify the evolution trends of future topics by the Hidden Markov Model (HMM). The results show that the CIM technologies can be divided into 17 topics. At the present stage, the technologies related to the Internet of things (IOT), big data and data management are the focus of the research and development (R&D) of CIM patents. Compared with the software technology, further development is needed for the hardware technology supporting CIM, particularly in terms of information acquisition (cameras and sensors), storage, and information transmitters. This study deepens the understanding of the CIM-related technical categories, and clarifies the direction of the development and evolution of CIM technology, providing a strong support to decision-makers in urban management.