Sensomind at Microso Technology Center
Microsoft exhibits great use of technology at the Technology Centers around the globe. Sensomind is one of the solutions showcased at their Copenhagen center and shows how the cloud and the power of arti cial intelligence can be put to use with the purpose of increasing product quality and optimizing production processes for manufacturing companies of every type all over the world. At the Technology Center, visitors get to experience what it is like to be a modern plant manager in an Industry 4.0 world. The demo allows visitors to train a neural network that can detect aws in products of di erent kinds. At the stand, there are various types of fake plastic foods available for visitors to use when training their models. Using a simple and intuitive web interface, visitors can deploy their newly trained neural network into production and see it running live making predictions on products passing by on a conveyor belt at the stand. The predictions made on the products are being uploaded to Sensomind's solution in the cloud where the data are being visualized in an easy-to-use dashboard hosted in Power BI (https://powerbi.microsoft.com/). Power BI allows the visitor to dig into the data and make analyses on the predictions made. This enables the visitor in their function as a plant manager to get insights about the production and potentially identify pattern and causes for errors. At this stage, the data become very actionable, as the visitor can act upon the insights and resolve the issue causing the errors.
Michael Sass Hansen (Sensomind ApS)
Michael has been postdoc fellow at Harvard University in the Computational Radiology Laboratory (http://crl.med.harvard.edu/people/sass-hansen/index.php) led by Dr. Simon Warfield. He holds a PhD degree in Medical Image Analysis from the Technical University of Denmark and in 2010 he won the Danish Elite Research Award for his work during his PhD. In 2016 he co-founded the startup Sensomind where he is applying his knowledge and experience to use cases in the manufacturing industry.