Commuting 2.0

Accepted submission type(s): application

Quality of life is affected greatly by our usual day to day activities and how we commute to and from our place of work plays a big part. Fortunately, this chore has been made very easy by routing apps that use data and routing algorithms to tell us how to get from A to B. However, especially for bicycles, pedestrians, and other light traffic, there is a dimension overlooked by routing applications: conditions and weather. There is a wide array of observation and forecast data about our environment that can be used to provide a great service to commuters.

Background & context

  • This challenge is about helping urban living by using data on weather conditions
  • Parts of the weather information are INSPIRE data
  • Vaisala has participated in Junction 2018 with the theme “Actually Useful Weather”

Key issues or questions to answer/investigate

We are looking for teams to produce prototype routing applications that, broadly speaking, make use of “comfort” as a factor in the routing equation.

  • How can data be used to assess the comfort level of a path?
  • How can comfortable environment-friendly commuting be increased?
  • How to assess safety and conditions of paths using data?
  • How can the comfort/safety data be best used to help commuters?
  • Can these methods be applied to help someone who wants exercise instead of comfort

Required knowledge and skills

  • Experience with routing algorithms and software
  • Software development skills necessary to modify/augment the routing software
  • Practical experience of commuting with bicycles will probably help you

Offered datasets

  • Forecast data on current and future weather (FMI)
  • Current and historical data on measured weather (FMI)
  • HSY air quality sensor data (Vaisala)

The weather datasets are available at FMI WFS3 beta service. The data from FMI is licensed under Creative Commons Attribution 4.0

Other relevant datasets

  • OSM or other base map for urban routing
  • Elevation models (National Land Survey of Finland)
  • HSL Developer Community

New technologies to test or evaluate

  • Core data is delivered through an experimental WFS 3.0 server
  • Data is in a new JSON data model specifically for observations and measurements OMSF

Note. WFS 3.0 implementation list is available in the WFS/FES Github repository

Offered or suggested tools

  • Open source routing software

Desired outcome and presentation

  • Online demo or proof-of-concept software delivered through a web application is preferred
  • Ideas relevant for the challenge that was not implemented due to time constraints or technical issues should be included in a presentation
  • Comments on the data encoding (OMSF) and delivery method (WFS 3)

Offered benefits for the teams

  • Change to present the work results in the Inspire Helsinki 2019 event (for the finalist teams).
  • Free trip to the 2020 INSPIRE Conference for one person of the winning team.
  • Set of professional cloud-based spatial data processing and visualisation tools during the Challenge.


Roope Tervo (FMI), Jani Kettunen (Vaisala), Ilkka Rinne (Spatineo)

Watch the webinar

Webinar with more info about this challenge was held on Thu Jul 04 at 12:00 UTC