Development of an AR Navigation System “Smart Information & Mobility Town (SiMT)” in Commercial Facilities
DOI:
https://doi.org/10.51596/sijocp.v1i2.21Keywords:
AR, 3D scan, spatial recognition, digital twin, self-position estimationAbstract
In recent years, with the development of IT technology, various information services in cities have become convenient and easily obtainable for everyone. However, information support provisions for users in cities using these IT technologies are still not sufficient. Many of these technologies are aimed at the public, and not all have been optimised for persons with disabilities, such as wheelchair users, the elderly, pregnant women, those with strollers, and so on. There is also insufficient support to provide information needed to move around in public transportation facilities such as stations, airports, and extensive commercial facilities, which have become increasingly common in recent years in Japan. Therefore, in this study, we used AR technology to develop an application, “Smart Info. & Mobility Town” (SiMT), aimed at supporting movement in SAKURA MACHI Kumamoto, a commercial complex built in Kumamoto City, Kumamoto Prefecture, Japan in 2019. The research method is as follows. 1; Summarised the outline of the target facility, SAKURA MACHI Kumamoto. 2; Used AR technology to develop an application, “Smart Info. & Mobility Town” (SiMT), aimed at supporting movement in the commercial complex. 3; Conducted demonstration experiments, proposed future developments and possibilities of SiMT, and summarised this study.
SiMT, which was developed on a trial basis, uses a 3D map created from 3D scan data of SAKURA MACHI Kumamoto and utilises the camera function of a smartphone to synthesise CG images of routes from the current location to the destination to support users’ movements. We also developed this technology and conceived future technology development, such as support in the event of a disaster and support for the mobility of vulnerable road users.
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Copyright (c) 2021 Masataka Nakahara, Motoya Koga, Satoshi Fujimoto
This work is licensed under a Creative Commons Attribution 4.0 International License.