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How Oracle Cloud Is Helping Furano City Blast a Path Through The Snow

Rebecca English
PR Director

Oracle Autonomous Database and Oracle Analytics Cloud underpin IoT experiment aimed at helping one of the snowiest cities in the world keep moving 

If you picture a perfect winter scene, for many, that conjures up scenes full of fluffy white snow.  Few places in the world are able to deliver on this vision quite like the north of Japan.  Its unique geographical location sees cold Siberian air gather moisture from being pushed over the warm Sea of Japan before being ‘dumped’ on the country’s west coast and mountain ranges.  

While great for those visiting this well-developed ski resort, the traffic congestion it causes isn't just a nuisance for the people of Hokkaido prefecture’s Furano City, whose annual snowfall has averaged more than 550cm over the past five years – New York City averages just under 100cm per year1 and London less than 50cm2. It’s also a problem for the city's economy, in terms of productivity and cost.

To combat this, as part of the Hokkaido IoT Promotion Project, Furano City is undertaking an experiment using IoT data to look at how it can make its snow clearing activities more efficient.

The project aims to visualize snow clearing operations, by using real-time data from GPS devices fitted to six snow ploughs, across a two-month period from December 2020 to January 2021.  The data will be used to map out their operating patterns in order to optimize the travel routes and find ways to improve work efficiency by reducing work hours and costs.

This is essential as the city faces a shortage of personnel experienced in snow clearing work. Operating a snow plough requires experience and a good understanding of the local roads and weather conditions, and it has to be done in a short period of time, early in the morning, so as not to interfere with commuting and the school run. 

As Shigeki Nishino, General Manager of Smart City Strategy Office, Furano City, explained, “In the midst of a declining working-age population, diversification of citizen needs, natural disasters, infectious diseases, and other unforeseen circumstances, Furano City is rolling out a variety of measures based on the basic principle of Smart City Furano, where people, goods, and information are connected, with the aim of creating a digital society in which all citizens can enjoy the benefits of ICT. This IoT experiment to demonstrate improved efficiency around our snow clearing efforts utilizes Oracle Autonomous Data Warehouse and Oracle Analytics Cloud to enable the collected data to be easily analyzed in a variety of patterns and visualized with simple operations. We hope that this initiative will improve the efficiency of snow removal and clearance operations. We will continue to accelerate initiatives, such as the use of ICT, to make our "smart city" where citizens can live in a more comfortable environment.”

The advanced data management platform comprises Oracle Autonomous Data Warehouse and Oracle Analytics Cloud, and is being implemented by technical partner, TIS Hokkaido.  It will correlate and analyze the operational data collected during the period as well as bring in citizen feedback, weather data, other related information such as patrol car dispatch records, and operational results from previous years, to help determine the optimal driving routes and work hours and to help identify areas for potential cost reduction. 

Oracle Autonomous Data Warehouse will provide a low-cost, highly reliable, secure, cloud data management platform that will help get the project up and running quickly, as it autonomously provisions, configures, protects, tunes, scales, patches, backs-up, and repairs a data warehouses environment.  It also supports multi-model data, analytical SQL, machine learning, graphs, and spatial analytics – so, for example, the team can easily measure the distance from the route of a snowplow vehicle. 

Oracle Analytics Cloud, which provides data visualization and predictive analysis, will enable the team to rapidly roll out online interactive dashboard and reports, as well as tap into machine learning algorithms for forecasting. 

Based on the results of the experiment, the aim is to apply the results to improve the operational efficiency of other vehicles, such as garbage trucks, and promote the realization of smart mobility. It is also intended to extend the scope of the project to collaborate with other regions so as to further improve the efficiency of the snow clearing activities. 

[1] https://www.currentresults.com/Weather/New-York/Places/new-york-city-snowfall-totals-snow-accumulation-averages.php

[2] https://www.currentresults.com/Weather/United-Kingdom/snowfall-annual-average.php


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