Mobilaris & Lule University of Technology working together to improve AI-based positioning in mining – International Mining

Posted by Paul Moore on 20th February 2021

Mobilaris recently initiated a collaboration with Lule University of Technologys project Applied AI DIH North. The purpose is to identify, apply and demonstrate different AI methods regarding positioning information. The goal is to develop the ability and accuracy of the companys existing solutions for mining and tunnelling applications and look at how new services and products can be created. The collaboration will last for two years and is led by George Nikolakopoulos, Professor of Robotics and Artificial Intelligence at Lule University of Technology.

The Applied AI DIH North project aims to create a strong innovation system for growth in the AI industry, a Digital Innovation Hub as a base, in collaboration, research, innovation, applied test-driven development, education and cluster formation. The project lasts for three years and is financed by the EUs regional development fund (Tillvxtverket), Lule University of Technology, Lule municipality, Skellefte municipality and the Norrbotten Region.

Daniel Enstrm, CTO at Mobilaris says: At regular intervals, there are technologies that not only simplify and improve existing solutions but that also open up completely new fields of applications that could not have been built before. AI is one such example and we at Mobilaris have it as a strong part of our future technology portfolio. The collaboration with the university is really excellent for us in this context. If we succeed, we will have several new applications we can productize and add to our portfolio with direct benefit for our customers. It is about both autonomous system monitoring and a new generation of positioning techniques. We really like the approach from the university, quick decisions, straight path to project start and focus on applications.

Finding discrepancies in distributed localisation systems will be part of the project. Deviations in this case would be, for example, unnatural movements for a particular entity or person that do not conform to natural behaviour. Obtaining positioning information on a global scale, based on sensors on a local scale or in existing infrastructure for positioning and communication has a growing demand. Many location algorithms designed for this purpose base their function on different types of built-in sensors and have been created in many different systems to provide location, such as WiFi, GPS, etc. However, these systems and sensors are vulnerable to variations in operating conditions and surrounding environments. There are many factors that can limit performance, eg inaccessible GPS environments or outdoor operations with poor GPS reception.

Michael Nilsson, Lule University of Technology Project Manager, says: It is great to start another sub-project with a business focus. We aim to become a strong region in applied AI and here we are now breaking new ground. Mobilariss focus and participation contributes to one of our goals, namely to become a European Digital Innovation Hub with a profile in the process and manufacturing industry.

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Mobilaris & Lule University of Technology working together to improve AI-based positioning in mining - International Mining