Digital Twin Computing of Things Opens Up a New Society

(1) Geospatial digitization technology (for infinitely extending objects with no portability)

(2) Technology for digitizing buildings (for huge objects with no portability)

(3) Technology for digitizing things (for objects of various sizes with portability)

2.1 Geospatial digitization technology for infinitely extending objects with no portability

A geographic information system (GIS) has been used for digitizing geospatial information about wide areas, such as cities, topographical information, and additional information in an integrated manner. Topographical information is digitized by extracting shapes from aerial radar and satellite images. In addition to this topographical information based on the coordinate system using latitude, longitude, and altitude, layers are prepared for each analysis target (such as a plane map and its topographical information, borders, and features), and they can be overlaid. These types of information are suited for representation in a macroscopic perspective because they have the number of characteristic points and degree of accuracy with which a wide range of information can be drawn at a practical speed.

2.2 Technology for digitizing buildings for huge objects with no portability

Building-information modeling (BIM) and construction-information modeling (CIM) have been used for designing the structures of features, such as buildings, roads, and bridges, as 3D models. BIM/CIM also manages attributes such as materials used in buildings and their strength. For constructing a real building, this technology is excellent at representing a microscopic perspective because of its high accuracy. It is also possible to represent a city by placing 3D models created with BIM on a GIS (Fig. 1), and there has been a trend toward making such a model available—together with the GIS—as an open-city model [1, 2].

Fig. 1. Example of creating a city model based on a 3D model using GIS and BIM.

2.3 Technology for digitizing things for objects of various sizes with portability

Computer-aided design (CAD) is used to design the structures of various industrial products as 3D models. Using CAD makes it possible to check interferences between objects and measure strain using physical simulation before manufacturing an actual product. For manufacturing real objects, the technology is excellent at representing a microscopic perspective due to its extremely high accuracy. However, the data format differs across various industrial fields and is not standardized.

Photogrammetry technology [3] (Fig. 2), which estimates feature points from moving images of objects and creates 3D models from these points, and shape-extraction technology by radar measurement have been proposed [4]. While there is an advantage in that all objects can be modeled in 3D from images, the extraction accuracy depends on the state of the environment, such as lighting level, and there are still many challenges with real-time extraction of moving objects in video processing.

Fig. 2. Example of extracting a 3D model by using a tool (Meshroom) implemented with photogrammetry technology.

4.1 Wide-area simulation

Simulation of a city includes simulation of people living in the city and their activities, transportation (cars, etc.), and environment (weather, etc.). Tokyo is taken as an example city. Central Tokyo has a population of over 13 million and over 3.5 million vehicles on its streets [5, 6]. Since it is not realistic to conduct these simulations on a single computer, it is possible to, for example, divide Tokyo into several areas, and subject each area to parallel distributed processing. However, in this case, it is necessary to consider people and vehicles moving across these areas of parallel distributed processing (Fig. 3). We are researching wide-area simulation with which movement across such areas is assumed.

Fig. 3. Example of a vehicle moving across areas of parallel distributed processing.

4.2 Highly accurate simulation

When simulations are used for real-time optimal control of activities of an entire city and for planning and decision-making by cities and governments, it is essential to improve the accuracy of the simulation results. Therefore, it is possible to improve simulation accuracy by including computational elements that have not been considered in the simulation thus far, for example, wind flow passing between buildings, a building’s exposure to sunlight, activity of each citizen, and movement of each car. However, if the number of such calculation elements is simply increased, the calculation amount will increase exponentially; therefore, we are clarifying which calculation elements have a significant effect on the simulation results and studying how to incorporate them into the simulation.

It is also necessary to consider fluctuations in simulation results caused by uncertain phenomena that cannot be easily predicted from past events, such as traffic accidents and heavy rain. To execute a simulation considering these uncertain events, it is necessary to not only execute numerical analysis on a computer but also reflect the events that occurred in the real world in the simulation calculation in real time to bring the calculation results closer to the events in the real world. We are currently researching technology to satisfy these requirements (Fig. 4). Through these efforts, we aim to enable large-scale, high-resolution, and highly accurate city simulations, which will be useful for optimizing city activities and human decision-making.

Fig. 4. Simulation using phenomena in the real world.