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Eugene Lisovskiy
CEO of MAPS.ME
Artificial Intelligence, Neural Networks,
Augmented Reality and Robotics:
New Challenges for OSM.
❖ 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
Trends In Imagery
Industry
SpaceX – Dropped World Prices for Satellite launch
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.
30cm/pixel Imagery by Digitalglobe (WorldView-4)
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).
Hi-res Aerial Imagery by Bing in Spain
Neural Networks
Educated by OSM
Community
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.
Roads recognized by Facebook IA
IA must be educated by humans
Mind-blowing 3D Views by Google...
AI... what?
Dashcams And
Navigation With
Augmented Reality
(AR)
AR navigation by Sygic
Onboard ARKit in iOS 11
Commercial Points
Automated Imports
POI Data Partners
Sell Map Data
Sell Location Based
Marketing Services
Navads – 60k Shell Gas Stations
Video/radar/lidar data
from semi/self driving
cars/robots
Self-driving cars computer vision building a map
Robots need good onboard maps
Robots are good mappers
Outdoor robots by Boston Dynamics
Goods Delivery Robots
OSM Marathon 2025
Regular mobile maps
users data
(GPS traces & POIs)
❖ 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
How to Map Faster?
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?
Google Maps: 1B Billion users = 1M POI Mappers
Google Maps: Engagement, Loyalty, Direct Marketing
Facebook: Suggest Edits
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
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.
Thank you!
Eugene Lisovsky, CEO of MAPS.ME
State of the Map Asia 2017

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Eugene Lisovskiy, CEO, MAPS.ME | SotM Asia 2017 |The Future of OSM in Asia and Beyond

  • 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
  • 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
  • 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...
  • 19. POI Data Partners Sell Map Data Sell Location Based Marketing Services
  • 20. Navads – 60k Shell Gas Stations
  • 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
  • 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
  • 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