1. Eugene Lisovskiy
CEO of MAPS.ME
Artificial Intelligence, Neural Networks,
Augmented Reality and Robotics:
New Challenges for OSM.

2. ❖ Trends in imagery Industry
❖ Neural networks educated by OSM community.
❖ Dashcams and Navigation with Augmented Reality (AR).
❖ Commercial data automatic imports.
❖ Regular mobile maps users data (GPS traces & POIs).
❖ Video/radar/lidar data from semi/self driving cars/robots.
❖ Summary: The Future of OSM Mapping
Agenda

3. Trends In Imagery
Industry

4. SpaceX – Dropped World Prices for Satellite launch

5. Satellite Imagery
Pros:
❖ Cheaper low-orbit satellite launch (thank to SpaceX).
❖ Higher resolution imagery (30cm/pixel already).
❖ No problems with governments.
Cons:
❖ 2 years to launch new satellite, still expensive (min $62M).
❖ 1 satellite captures the whole earth in 2 years.
❖ Not enough resolution to read road and street signs.
❖ Clouds, trees.

6. 30cm/pixel Imagery by Digitalglobe (WorldView-4)

7. Drones Aerial Imagery
Pros:
❖ Higher resolution imagery (up to 1 cm/pixel).
❖ Cheap & easy-to-use.
❖ Under the clouds + daily snapshots.
Cons:
❖ Low area coverage. Many drones required.
❖ Security regulations for capturing cities.
❖ Unstable quality (different drones, angels, resolution).

8. Hi-res Aerial Imagery by Bing in Spain

9. Neural Networks
Educated by OSM
Community

10. AI and Neural Networks
Pros:
❖ Well educated AI recognise images better than human.
❖ No supercomputer required. Community laptops is enough.
❖ Can work with standard imagery, lidar, radar data.
Cons:
❖ No cons, obviously.
❖ Hi-res source data required for better results.
❖ Still the humans need to verify and educate AI.

11. Roads recognized by Facebook IA

12. IA must be educated by humans

13. Mind-blowing 3D Views by Google...

14. AI... what?

15. Dashcams And
Navigation With
Augmented Reality
(AR)

16. AR navigation by Sygic

17. Onboard ARKit in iOS 11

18. Commercial Points
Automated Imports

19. POI Data Partners
Sell Map Data
Sell Location Based
Marketing Services

20. Navads – 60k Shell Gas Stations

21. Video/radar/lidar data
from semi/self driving
cars/robots

22. Self-driving cars computer vision building a map

23. Robots need good onboard maps

24. Robots are good mappers

25. Outdoor robots by Boston Dynamics

26. Goods Delivery Robots

27. OSM Marathon 2025

28. Regular mobile maps
users data
(GPS traces & POIs)

29. ❖ 170 thousand users
❖ 1 million new POIs
❖ 600 thousand updated POIs
❖ 200 thousand notes
❖ 235 countries mapped
1,5 years POI mapping in MAPS.ME

30. How to Map Faster?

31. 1. Acquire new mappers:
➢ Mapathons, SOTM
➢ Working with schools and students
2. Engage existent mappers:
➢ Direct (email/push) marketing
➢ Gamification, loyalty programs & activities
3. Start Using AI:
➢ Hi-res satellite and aerial imagery
➢ Develop algorithms, Educate Neural Networks
4. Partner with Self/Semi driving cars providers
How To Engage More People Into Mapping?

32. Google Maps: 1B Billion users = 1M POI Mappers

33. Google Maps: Engagement, Loyalty, Direct Marketing

34. Facebook: Suggest Edits

35. More MAPS.ME Users = More Active OSM Mappers
Hardcore
OSM
Mappers
Casual POI
Mappers
New Mobile Maps
Users
Mobile mappers are 18 times more
active than regular mappers.
OpenStreetMap.org
❖ 4000k registered mappers
❖ 30k monthly active mappers
❖ 0,8% of active mappers
MASP.ME
❖ 176k registered mappers
❖ 25k monthly active mappers
❖ 14% of active mappers

36. The Future of OSM Mapping (2020+)
POIs details (contacts, services) along
streets and inside buildings.
Roads details (lines, limits,
surface), building details
(street name, building
numbers).
Buildings,
roads, rivers,
forest, terrain,
1. Satellite + AI + Humans education
Source: hi-res satellite/aerial/drone imagery open network.
Processing: automatic IA recognition + verification and neural
networks education by humans.
2. Cars + AI + Humans education
Source: imagery, lidar, radar data from self/semi driving cars.
Processing: automatic IA recognition + verification and
neural networks education by humans.
3. Humans + AI validation
Source: data partners, mobile edits + user images
Processing: collaborative human validation.

37. Thank you!
Eugene Lisovsky, CEO of MAPS.ME
State of the Map Asia 2017