Gävle Citysamverkan becomes Collabs in Gävle Innovation Arena today

Today we signed a project partner agreement with Gävle Citysamverkan. The parties agree that Gävle Citysamverkan delivers sensor data about visitor statistics in the center of Gävle, events and activities in the city, also information on physical barriers such as road or buildings constructions and other things that effects traffic flow and people’s movement. These data will ultimately be used in the model of the city (digital twin) for visualization of movement patterns in the city. In general, this will provide opportunities to create new innovations and applications that in turn lead to sustainable urban development from a central perspective.

Gävle Citysamverkan is a non-profit association which owns "Gävle Citysamverkan Service AB" in which the operational activities are conducted. The current organization was formally formed in 1997. At present, the number of members is about 200 property owners, companies, organizations and authorities.

The project partner is particularly interested in how Gävle Innovation Arena together with Citysamverkan’s own data can be combined and applied to create new innovations and applications. Innovations and applications that in turn lead to sustainable urban development from a central perspective.

The sustainable urban development of the future can be supplemented by new ways, methods and knowledge. These new ways highlight citizens’ co-creation and citizen data in new ways. To increase well-being and people's willingness to stay in urban environments, we must know what factors affect this. What makes Gävle residents and other players want to stay in the center during all hours of the day. What in the place make Gävle residents feel comfortable and well-being?

Together, the parties want to investigate what creates pleasant and well-being in the city. By bringing together large amounts of data and analyzing this, we believe that it is possible to fold the impact of various factors on the perceived well-being and the desire to stay in the city. By bringing together these layers of data, we should also be able to create forecasts for how many people will move in the city in the future and thereby be able to plan based on this.

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