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Deep learning to create growth and five times quicker workflows for MapsPeople

Written by MapsPeople Finance | Jul 13, 2021 8:00:00 AM

The Innovation Fund grants MapsPeople 33% of costs for a new deep learning project aiming to streamline the production of maps for clients. What used to take five days will now be able to be carried out within one.

MapsPeople A/S | Press Release

MapsPeople is currently developing new deep learning-based algorithms, methods, and tools that can automatically recognize, analyze, and classify objects in technical drawings. The project is related to MapsPeople's recently mentioned patent pending. The use of deep learning-based methods is a cornerstone for MapsPeople when it comes to creating maps for indoor navigation solutions as the automation reduces a lot of manual tasks and speeds up the map production time by up to five times. The Innovation Fund has just announced that they will cover 33% of the project costs. 

"This project is essential for MapsPeople and our expansion. It will increase our scalability radically as we will minimize the time spent processing technical drawings. This is crucial for us in order to achieve our growth goals. MapsPeople will, simply put, become a stronger contestant on the global market as we will be able to manage much larger projects since our reaction time will be much shorter and more efficient. What used to take five days will now be able to be carried out within one," Says Michael Gram, CEO at MapsPeople, and adds:
"Our growth potential increases significantly when we suddenly can deliver maps day to day. With this project we expect to reduce the time spent creating maps down to 20% and the goal in the long run is 10%. This means that we will free up a lot of resources that can instead help increase the quality for clients and end-users as well as create more business for MapsPeople. With the grant from The Innovation Fund we can already this fall hire four additional employees and speed up the automation process notably."

Digital wayfinding is still in short supply

In a time where everything is digitized and where we can navigate large cities with the help of smart devices, it can be hard to understand that large buildings like airports, universities, and hospitals still do not have easily accessible indoor digital wayfinding. A report shows that 30% of missed appointments in hospitals are related to patients being late due to issues finding their way. 

MapsPeople has developed the MapsIndoors platform which can not only manage general wayfinding within complex buildings and infrastructures but also integrate with a large range of useful features in offices including booking of meeting rooms and desks. Quick delivery is an important competitive parameter and the new deep learning project will support MapsPeople in becoming a market leader within indoor navigation.

The new algorithms, methods, and tools are expected to be implemented within 14 months.

CONTACT INFORMATION

MapsPeople A/S

Michael Gram, CEO

Mobile (+45) 53 74 09 00

Email mg@mapspeople.com 

Stigsborgvej 60, 9400 Nørresundby

Certified Advisor

Grant ThorntonJesper Skaarup Vestergaard

Mobile (+45) 31 79 90 00

Grant Thornton Stockholmsgade 45 2100 Copenhagen Ø Denmark

Press

MapsPeople PR Agency

Mindshare

Andreas Hedensten, Communications Partner

Mobile: (+45) 2892 6494

Email: andreas.hedenstein@mindshareworld.com
 

ABOUT MAPSPEOPLE 

MapsPeople is a dynamic mapping SaaS company and a Google Premier Partner. MapsPeople is listed on Nasdaq First North Premier Growth Market. MapsPeople's dynamic mapping platform MapsIndoors helps employees find a desk or colleague in a large corporate office, assist guests navigate to their seats at stadiums, display vacant parking lots, or avoid long queues. With the MapsIndoors solution, employee productivity is improved, fan experience reaches new levels, and passengers do not miss flights or trains.

https://news.cision.com/mapspeople-a-s/r/deep-learning-to-create-growth-and-five-times-quicker-workflows-for-mapspeople,c3384348

https://mb.cision.com/Main/20415/3384348/1444498.pdf