Fujitsu showcase at Japan Mobility Show 2023 highlights solutions that contribute to sustainability and wellbeing

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Fujitsu will present a demonstration of a system that uses its social digital twin technology to predict and visualise natural disasters and their damage to support the creation of disaster-resilient, safe, and secure communities.

Tokyo, October 19, 2023 (JCN Newswire): Fujitsu today announced that it will exhibit at the Japan Mobility Show 2023, which will be held at Tokyo Big Sight in Japan from Thursday, October 26, to Sunday, November 5, 2023. Fujitsu will exhibit Ekimatopeia, a system for visualising ambient noise in stations for deaf or hard-of-hearing passengers using AI, as well as disaster resilience efforts through digital twin technology, underscoring its commitment to improving people’s wellbeing as part of its vision for Fujitsu Uvance. Fujitsu’s display is part of the Tokyo Future Tour, one of the show’s headlining events, which is based on the concept of a future Tokyo transformed by mobility.

On Saturday, October 28, from 13:00 to 14:00, Shunsuke Onishi, Corporate Executive Officer, SEVP, CRO of Fujitsu, will take the stage at the session “Global Environment x Future of Mobility” of the Japan Future Session, a series of presentations on the future of Japan.

Exhibition Overview

1. Ekimatopeia, which visualises station environmental sound using AI

The system uses AI to visualise environmental sounds, such as station announcements and the sound of trains running, as well as text, sign language, and onomatopoeia. Fujitsu is showcasing the system used for a field trial conducted at JR Ueno Station in Tokyo from June to December 2022 as a demo for this event. Fujitsu aims to contribute to the realisation of a safer and more secure travel experience for rail passengers and to promote mutual understanding of DE&I (diversity, equity, and inclusion) by providing customers who are deaf or hard of hearing and others enjoyable experiences at stations with Ekimatopeia.

FujitsuMobilityFig1

2. Disaster resilience efforts through digital twin technology

Fujitsu will present a demonstration of a system that uses its social digital twin technology (1) to predict and visualise natural disasters and their damage to support the creation of disaster-resilient, safe, and secure communities. Fujitsu aims to realise a resilient society by actively redesigning the future using digital rehearsal technology (2) that reproduces predictions of possible future disasters, verification of evacuation guidance and rescue routes, and verification of early recovery after disasters in a digital space.

FujitsuMobilityFig2

The Japan Mobility Show 2023 is the first event in four years since the Tokyo Motor Show and is organized by the Japan Automobile Manufacturers Association, Inc. (JAMA) with the concept of creating the future of mobility together with new partners, including other industries, startups, and visitors beyond the automotive industry.

Venue: Tokyo Big Sight < East/West/South Halls (Address: 3-11-1, Ariake, Koto-ku, Tokyo, Japan) Fujitsu will exhibit in the Tokyo Future Tour area of West Halls. Dates (show period): October 26 (Thu) to November 5 (Sun) For more information: https://www.japan-mobility-show.com/en/outline/

[1] Social digital twin technology: A group of technologies being researched and developed by Fujitsu that can digitally reproduce not only the state of people and goods but also entire economic and social activities based on real-world data. In addition to understanding the actual conditions of society and the mechanisms by which problems arise, it contributes to the formulation of policies to solve diverse and increasingly complex problems.
[2] The digital rehearsal technology: The world’s first technology being researched and developed by Fujitsu that can reproduce the behaviour of people and society in the urban stage of the digital space on the digital twin before the actual application of the measures in the real world and search for the optimal measures by grasping the effect and impact of the measures.

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