• Energy Research

With the development of the online platforms and the Internet of Things (IoT), various transportation services have been provided, and the lifestyle of the general public has changed significantly. However, the speed of development of technologies and services for the mobility handicapped has been relatively slow. Accordingly, in this paper, the smart mobility patent data for the mobility handicapped is subdivided through clustering to derive the mobility handicapped-related vacant technologies, and the prospect of the vacant technology is verified. For each cluster, a technology level map is generated in consideration of the technology growth level and the scope of authority of the vacant technology derived through the generative topographic map (GTM) patent map, and the level of the vacant technology is checked in terms of quantity and quality. Both indicators perform time series analyses on superior technology to predict technology trends and determine the technology’s promisingness. Unlike the precedent studies that focused only on quantitative analysis methods, this paper identified the usefulness of the technology through clustering and various verification processes and materialized it as a vacant technology that is applicable to actual R&D. Accordingly, through this empirical paper, it is possible to understand the current level of vacant technology in smart mobility for the mobility handicapped and establish an R&D strategy to prevent monopoly in technology in the future market and maintain competitiveness. It can also be utilized for new technology development in consideration of convergence with currently developed technology.

The rapid advancement of digital technologies has fundamentally changed the competitive dynamics of the logistics industry. For players in the logistics industry, digitization has become an unavoidable situation to achieve survival and sustainable competitiveness. A technology strategy is essential for digitization, and identifying opportunities and threats of technology development through technology trend exploration is important for technology strategy. In addition, to enable the implementation of the technology strategy, it is necessary to detect the change in technology and search for the technology that is expected to have a practical development effect. The purpose of this study is to identify opportunities and areas for technology development through patent data in establishing technology strategies. Previous research mainly relied on the expert interview method, and there was also a patent analysis study based on topic modeling, but only to grasp technology trends. This paper aims to propose a new framework for the extension to the stage for establishing a technology roadmap. By using the Word2Vec algorithm, we will investigate the patent search formula that reflects the trend, the prediction of changes in logistics technology through LDA (Latent Dirichlet Allocation) clustering of patent data, and the derivation of vacant technology by experimental methods. The proposed framework is expected to be utilized for predicting technological change and deriving promising technologies for establishing technology roadmaps in logistics companies.

As life expectancy increases, the number of people who suffer from blind and visual impairment due to presbyopia is gradually increasing. Assistive device systems have been used to overcome various physical, social, infrastructure, and accessibility barriers. As technology has advanced, the scope of assistive technologies has been expanded. Therefore, we explored technological opportunities in assistive technology for the blind and visually impaired to establish a strategy for the technology competition in the near future. Firstly, the patent vacuum is detected by generating the patent map based on generative topographic mapping (GTM). Secondly, social network analysis is applied to identify the relationship between patent vacuums and occupied grid points in the patent map. Finally, the technology activity index and technology impact index are considered at quantitative and qualitative levels. Consequently, it was identified that wearable devices, including the road situation signal acquisition module and data acquisition process control module, could be occupied in the future. This study can provide practical ideas for research and development (R&D) in the field of assistive devices for the blind and visually impaired. In addition, this study can be an ample source for decision/policy makers to project new contents.

In this study, we suggest methodologies for identifying promising and vacant technologies on smart farms by analyzing patent information. Additionally, a technology roadmap for smart farms is suggested using network analysis. The database of patents related to smart farms was extracted from the United States Patent and Trademark Office (USPTO) by keyword search, and valid patents data was selected and clustered using the Latent Dirichlet Allocation (LDA) algorithm. We also conducted the technical importance analysis and trend analysis to identify promising technology topics. By developing a patent map based on a self-organizing map (SOM), we were able to identify vacant technologies among smart farm technology groups. In order to develop vacant technologies, we presented a stepwise technology roadmap by analyzing the relationship between technology elements using network analysis. The proposed procedure and analysis method provides useful insights in establishing research and development (R&D) strategies for the development of smart farm technology roadmaps.