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| Tuesday, 19 July 2016, 08:40 HKT/SGT | |
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Source: Fujitsu Ltd | |
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| Providing predicted train delay times to users of Jorudan's "Norikae Annai" App |
TOKYO, July 19, 2016 - (JCN Newswire) - Fujitsu Limited today announced that it has collaborated with Jorudan Co., Ltd. to add a train delay time prediction function, using AI machine learning technology, to Jorudan's "Norikae Annai," a service that provides public transportation route-planning information. It is also carrying out a field trial of this service in support of public transportation users in their choice of routes across 138 train lines in the Kanto region, starting today until September.
 | | Figure 1: Summary of the field trial system |
This functionality is provided as the cloud service FUJITSU Intelligent Society Solution SPATIOWL(1), which embeds a delay time prediction engine - jointly developed with SRI International(2), one of the world's pre-eminent research organizations - into the Fujitsu AI technology, Human Centric AI Zinrai(3). Delay time predictions with enhanced accuracy are provided by having the service learn from data, such as that from railway operations(4) and from past data about railway operations submitted by users(5) to Jorudan's Norikae Annai service. This enables users of the Norikae Annai app to have more accurate and timely predictions about train delay times than before, making it useful for them to choose a route.
Going forward, Fujitsu aims to verify the function's effectiveness through this field trial, and will look into expanding the service both inside and outside Japan.
Background
In Japan's urban rail system, trains are commonly delayed by sudden accidents or disasters. When this happens, alternative or replacement transportation is offered through other public transport methods, such as other train lines or buses. At the same time, this creates a problem for users when they need to think about how to most effectively reach their destination, as it is difficult to make the decision of whether to wait for the delayed train's service to resume, to change to another train line, or to pick another option. Despite lacking experience in rail operations, Fujitsu wanted to provide public transit-related business operators with information that supports users' choice of routes by learning from past delay information, and to verify its effectiveness in this field trial.
Trial Summary
Jorudan's Norikae Annai service is used by about 10 million people per month in Japan (according to a March 2016 report) to easily find routes, fares and estimated travel times for modes of public transportation.
Fujitsu will now provide predicted train delay times using AI technology for the Norikae Annai service and verify prediction effectiveness. Using machine learning technology and provided through SPATIOWL, the service is made to learn from past railway operations data and data submitted by users, and predicts changing delay times based on newly submitted data and current operational information. These predictions are displayed in the route search results in Jorudan's Norikae Annai app, supporting users' route selection when trains are delayed.
Trial period:
July 19, 2016 to end of September 2016(6)
Goals:
1. Verify the effectiveness of support for users' choice of action
2. Verify the effectiveness of predictive functionality for train delay times
Application:
Norikae Annai app on Android
Train lines covered in the trial:
Lines through Tokyo, as well as Kanagawa, Saitama and Chiba prefectures (with some exceptions, 138 train lines in total)
Features of information provided:
Using AI Zinrai technology for increased accuracy of predictions based on machine learning using accumulated data.
Future Developments
Based on the results of the current field trial, Fujitsu aims to continually improve prediction accuracy, and is planning to develop it as a new service for SPATIOWL.
(1) SPATIOWL
A service that provides new value using large volumes of location information collected from sensor information from vehicles in transit (information such as speed and location collected from vehicles in transit, treating the vehicle itself as a sensor), information about people and facilities, sensor information, and information from the internet.
(2) SRI International
Headquartered in Silicon Valley, SRI International is an independent, non-profit research center that creates world-changing innovations making people safer, healthier, and more productive. SRI brings its innovations to the marketplace through technology licensing, spin-off ventures and new product solutions. For more information, please see http://www.sri.com.
(3) Zinrai
Zinrai brings together and systematizes the Fujitsu Group's experience and technology - the results of its R&D related to AI - in such areas as sensing and recognition, knowledge processing, and decision support, as well as the machine learning that makes these more advanced and mature.
(4) Railway operation data
The field trial uses railway operation data provided by Rescuenow Inc.
(5) Submitted information
The field trial uses information provided by Jorudan, submitted by users in Jorudan Live!
(6) Trial period
Certain situations may lead to the field trial being cancelled without notice.
Contact:
Fujitsu Limited
Public and Investor Relations
Tel: +81-3-3215-5259
URL: www.fujitsu.com/global/news/contacts/
Topic: Press release summary
Source: Fujitsu Ltd
Sectors: Logistics & Supply Chain, Cloud & Enterprise, IT Individual
http://www.acnnewswire.com
From the Asia Corporate News Network
Copyright © 2024 ACN Newswire. All rights reserved. A division of Asia Corporate News Network.
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