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Predictive Movement

Reference number
Coordinator Luleå tekniska universitet - Institutionen för system- och rymdteknik
Funding from Vinnova SEK 10 000 000
Project duration January 2020 - December 2021
Status Completed
Venture Challenge-driven innovation - Phase 2 Collaboration

Important results from the project

Predictive Movement aims to create a digital competition neutral platform that will act as a collaborative hub for the transports of people and goods with the help of artificial intelligence (AI). In its first phase, the project will solve the societal challenge of parcel deliveries in rural areas. The project has developed a functioning digital platform according to the goal description. In addition, we have developed a digital twin to gain an understanding of the disruptive ideas the platform stands for and to facilitate implementation.

Expected long term effects

The project has developed an AI-based platform for coordinating goods. The technology has been tested in Ljusdal and the coordination in Pajala. Difficulties in the business models were identified during the process, which led us to develop a digital twin that was applied in Arjeplog and Västervik. In Västervik, drone transports were also tested. The project has also proposed a new business model for parcel deliveries and assisted with concrete proposals for new regulation of the industry.

Approach and implementation

The development of the platform has followed an exploratory process, based on users needs and was followed by small-scale experiments that were tested on the users to learn more about problems and obstacles. Three real life tests have been carried out developing PM. The tests showed that the most profound obstacle was fear of change and acceptance for new business models. This led to the development of a digital twin where tests can be done in a virtual environment. During the third real life test an innovation process was carried out for the development of the new business model.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 11 February 2022

Reference number 2019-04727