Flictec Inc. is a Japanese mobile application development company. They have been avid users of our Mobile SDK and the CARTO platform for many years. One of the solutions they provide is an advanced traffic and navigation application 渋滞ナビ or Jyutai Navi (Japanese for traffic jam navigator) with millions of happy end-users you can call it the “Waze of Japan.”
How it works:
Probe data is collected from users smartphones and recorded into CARTO so they can get traffic insights by spatially analyzing probe data with road networks. Flictec has been collecting data since 2013 and the total number of collected records has reached more than 10 billion. Currently they add 30 million records per day that span across Japan. Flictec also keeps all of its data and uses it to predict future traffic jams. Now they have 8TB in CARTO making it one of the largest CARTO single database instances. To avoid slowing they do partitioning every 12 hours and use additional databases for map-matching analysis.
Here is real time probe data from Jun 13 2016 at 8 a.m. to 9 a.m. as recorded in CARTO for the center of Tokyo:
Each data point indicates location speed and bearing. Using CARTO they've plotted the very slowest cars as red slower cars as orange faster as blue and the fastest as green.
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Jyutai Navi provides the following key features:
- A traffic information map (powered by our Mobile SDK)
- All data is saved in CARTO on the cloud
- Traffic layers are drawn using CARTO Maps API
- POI and labels are taken from the server through the CARTO SQL API
- Car navigation
- Routes are calculated on the server. Their routing engine considers traffic situations and finds the fastest route
- Route lines are drawn on the map as a layer of the Mobile SDK
- The app uses 6 layers at the same time and loads a lot of objects but our SDK is still really fast!
This is a very exciting use case for CARTO! Seeing a customer merge our web and mobile technologies long before we were united and really stretch our technical limits in several ways is very inspiring to us. We wish them the very best in their solution and will keep looking for other cases like this!
Happy mobile data mapping!