Projects

MarshallAI’s pilot project helps to understand, maintain and assess the demand for and future needs of bicycle parking services. Anonymous real-time data can be collected on the use of bicycle parking facilities using computer vision and video automation. The solution monitors the utilisation rate of bicycle parking facilities, bicycles parked at parking facilities for an extended period of time, as well as the number of bicycle thefts or attempted thefts.

The Norwegian Bikeloop AS‘s smart bicycle parking solution is a secure modular bicycle locker for eight bicycles. Booking bicycle parking is possible for anyone via their app. The bicycle locker design takes special groups into account, and the lights and voice guidance make the locker accessible.

In Gispo‘s experiment, the goal is to increase the potential use of the city’s 3D materials by enabling the utilisation of 3D data in QGIS for a wider user base within the city organisation. 

Webion participates in the experiment with the aim of developing the measurement of urban spaces. The technologies in the experiment can be used in the future to produce measurements of urban spaces that promote the development of digital twins of cities as well as maintenance. In the experiment, among other things, street-level imagery is refined using artificial intelligence. 

Sitowise is developing a new and easily scalable method in which data from various traffic infrastructure sources is analysed and classified automatically using commercial tools and artificial intelligence algorithms. 

The results of the pilot procurement will be used for the implementation of the CityGML 3.0 street environment test data in 2024.  

The project involves using light radar technology (lidar) to gather data on vehicles, bicycles, electric scooters, and pedestrians. The aim is to understand the impact of the changes on the Esplanadi on traffic flow and traffic behaviour.  

In a pilot conducted by Sitowise, the goal was to produce a 3D model of the urban environment, which can be utilized in examining various modes of transportation environments in Helsinki. The method used in the pilot was a continuation of Sitowise’s work created in the spring of 2022, where a tool was developed using the FME conversion process to transform road features from the General Area Registry (YLRE) into CityGML format. 

Zero Gravity was developing a way to combine existing City of Helsinki data on traffic areas with manual labelling for the training dataset as well as creating a segmentation model to extend to the rest of pilot area.

The pilot with Marjetas Academy is one of the agile pilots selected in Oct 2022 (read more in Finnish) which aim to support the development of Helsinki’s cityinfra platform.

The pilot with Normiopaste is one of the agile pilots selected in Oct 2022 (read more in Finnish) which aim to support the development of Helsinki’s cityinfra platform.

This pilot is one of the selected agile pilots from the call in the summer of 2020.

This project is one of the selected agile pilots. The solution will be tested in the spring of 2021 as the first phase of the agile pilot process.

This project is one of the selected agile pilots. The solution was tested in the spring of 2021 as the first phase of the agile pilot process, the second phase of the pilot is planned for spring of 2022.

This project is one of the selected agile pilots. The solution was tested in the spring of 2021 as the first phase of the agile pilot process.