World's first vibration sensing technology using telecommunicaiton optical networks for making road snow removal decisions in heavy snowfall area

Aiming to solve regional issues using environmental information obtained from communications infrastructure

Tokyo - Nov. 10, 2023 - NTT Corporation (NTT), NTT EAST Corporation (NTT EAST), and NEC Corporation (NEC) have jointly applied optical fiber vibration sensing technology to construct a machine learning model that estimates road surface conditions from vibration characteristics transmitted through communication optical fibers ^[1] already installed underground. (The demonstration experiment was conducted in Aomori City from November 2022 to March 2023 and is scheduled to continue this winter.) As a result, we can expect to DX urban patrol work and snow removal decisions before road snow removal, which are major regional issues in heavy snowfall areas. In the future, using this technology, we will promote the generalization of machine learning models to deal with all snow conditions in heavy snowfall areas. We will also use optical fiber sensing technology to acquire environmental information about the city, aiming to solve various local issues. These results will be exhibited at the NTT R&D Forum - IOWN ACCELERATION ^[2], which will be held from November 14^th to 17^th, 2023.

Figure 1 Overview of Snow Removal Decisions by Vibration Sensing Technology Using Telecommunication Optical networks

1. Background and purpose

In heavy snowfall areas, snow removal measures are important to maintain urban functions and ensure smooth traffic so as not to interfere with the daily lives of residents. The road snow removal work is mainly carried out in the midnight zone. To maximize the effectiveness of snow removal operations within a limited time, city patrols are conducted during the daytime, and snow removal decisions are made daily for an area called a snow removal zone based on the amount of snow, snowfall forecast, and investigator's rules of thumb. However, as the population ages and declines in rural areas, there is a shortage of snow removal operators to make road snow removal decisions ^[3]. Improving efficiency through DX is an urgent issue. In response to this regional challenge, the three companies conducted a demonstration experiment to determine the implementation of snow removal by combining NEC's vehicle speed detection algorithm with NTT's proposed correlation analysis method of snow removal necessity and traffic vibration characteristics with traffic vibration data of city roads in Aomori City obtained using unused underground optical fiber installed by NTT EAST and optical fiber sensing technology provided by NEC.

2. Features of this technology

3. Overview of demonstration experiments

4. Results of demonstration experiments

Taking advantage of the fact that optical fiber for telecommunication is installed in the underground of city roads in snow removal zones, we succeeded in determining snow removal in multiple snow removal zones by analyzing traffic vibration data obtained by optical fiber vibration sensing technology.

Figure 2 Snow removal necessity decision model

5. Roles of each company

6. Outlook

Based on these results, the three companies will continue to conduct experiments in areas with different regional conditions to demonstrate the versatility of the snow removal necessity decision model, and will aim to solve problems in areas with heavy snowfall, such as maintaining a sustainable road snow removal system by making real-time snow removal decision DX. In addition, we will promote co-creation activities toward the establishment of optical fiber sensing application technologies that can solve local issues by analyzing urban vibration data and environmental information that can be collected using the communications infrastructure.

< Glossary >

^[1]Unused and inactive core wires in a communication optical fiber line

^[2]"NTT R&D FORUM 2023 -IOWN ACCELERATION" Official Website
https://www.rd.ntt/e/forum/2023/

^[3]Reference: Request for measures against snowy and cold areas concerning the government budget for FY 2024 http://www.sekkankyo.org/R50602youbou.pdf

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