Multiscopic Topological Twin in Trailer Living Laboratory : Plenary Talk

Abstract

Recently Cyber-Physical Systems, Digital Transformation, and Digital Twin have been discussed towards the digitalization of service to people thanks to the integration of information, intelligence, communication, and robot technologies. topological structure is useful to extract features from given or measured big data and to simulate a real-world phenomenon in such a cyber world. Therefore, we proposed the concept of topological twin. The aim of topological twin is to (1) extract topological structures hidden implicitly in the real world, (2) reproduce them explicitly in the cyber world, and (3) simulate and analyze the real world in the cyber world. The topological twin plays the important role in extracting and connecting structures hidden in real world from the mutliscopic point of view. In this talk, we discuss the concept of topological twin for sophisticated service to people in order to bridge the cyber-physical gap from the multiscopic point of view. First, we discuss the role of trailer living laboratory as a new style of smart home in the future society. We can bring the trailer living laboratory to elderly houses, hospitals, and public spaces, and discuss the co-creation towards open innovation using daily life settings with multi-stakeholder approach. Next, we explain various types of topological mapping methods, unsupervised learning methods, and graph-based methods as the methodology of topological intelligence. One of them is Growing Neural Gas (GNG) that can dynamically change the topological structure composed of nodes and edges. We have proposed various types of methods based on multi-scale batch-learning GNG called Fast GNG. Next, we show the comparison result of Fast GNG with other methods. Furthermore, we show several experimental results of multiscopic topological twin in the trailer living laboratory. Finally, we discuss the future direction of researches on the multiscopic topological twin.