Urban computing uses data from cities to understand problems and create solutions. It involves collecting and analyzing large amounts of data from sensors, vehicles, buildings and people. This data can help address issues like traffic, pollution, and energy use. The Center for Urban Science and Progress in New York uses these techniques to improve commutes, emergency response, and air quality for New York City. Automatic map inference from imagery and GPS data can help update maps, which is important for transportation and routing services. Analyzing a city's road network can evaluate its robustness against failures or attacks.

1. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Artificial Intelligence and Big
Data Analytics for Cities
Sofiane Abbar, PhD
SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar

2. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Introduction to Urban Computing
UC is a process of acquisition, integration, and analysis of big and heterogeneous data
generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles,
buildings, and human, to tackle the major issues that cities face, e.g., air pollution,
increased energy consumption and traffic congestion.
Yu Zheng, Microsoft Research
UC uses data to better understand how cities work. This understanding can remedy a
wide range of issues affecting the everyday lives of citizens and the long-term health and
efficiency of cities — from morning commutes to emergency preparedness to air
quality. The urban issues CUSP takes on will be New York’s. The solutions it creates
will make the city more productive, livable, equitable, and resilient.
Center for Urban Science+Progress, New York City

3. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Introduction to Urban Computing
UC is a process of acquisition, integration, and analysis of big and heterogeneous data
generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles,
buildings, and human, to tackle the major issues that cities face, e.g., air pollution,
increased energy consumption and traffic congestion.
Yu Zheng, Microsoft Research
UC uses data to better understand how cities work. This understanding can remedy a
wide range of issues affecting the everyday lives of citizens and the long-term health and
efficiency of cities — from morning commutes to emergency preparedness to air
quality. The urban issues CUSP takes on will be New York’s. The solutions it creates
will make the city more productive, livable, equitable, and resilient.
Center for Urban Science+Progress, New York City

4. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Introduction to Urban Computing
UC is a process of acquisition, integration, and analysis of big and heterogeneous data
generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles,
buildings, and human, to tackle the major issues that cities face, e.g., air pollution,
increased energy consumption and traffic congestion.
Yu Zheng, Microsoft Research
UC uses data to better understand how cities work. This understanding can remedy a
wide range of issues affecting the everyday lives of citizens and the long-term health and
efficiency of cities — from morning commutes to emergency preparedness to air
quality. The urban issues CUSP takes on will be New York’s. The solutions it creates
will make the city more productive, livable, equitable, and resilient.
Center for Urban Science+Progress, New York City
Major Players

5. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Service Reachability in Cities

6. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Service Reachability in Cities
Understanding facility distribution in cities is of great importance
for urban planners and policymakers, as it relates to the design
quality of cities and the well-being of citizens.
Q1. What is the gap between actual and optimal distribution of
facilities in a city?
Q2. Determine under/over-served areas?

7. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar

8. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Actual vs. Optimal Distribution
● Split cities into blocks
○ Population Count for each block
● Actual Distribution
○ Compute Travel Time of each block to
closest facility
● Optimal Distribution
○ Find best placement of facilities such
that overall travel time is minimal
Toptimal/Tactual

9. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Spatial Analysis of Service DistributionDoha
Boston

10. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Automatic Map Inference

11. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Automatic Map Inference and Update
Automatic Map Inference from Satellite Images and GPS
traces is today a tedious process with many manual curation
steps. Up to date map are of paramount importance for:
● Government agencies
○ Traffic departments
○ Transportation planning
● Business
○ Taxi, ride-sharing, ride-hailing services
○ Self-driving vehicles
○ Routing-based services

12. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Automatic Map Inference and Update
Automatic Map Inference from Satellite Images and GPS
traces is today a tedious process with some manual curation
steps.
Partners & Data
+4K taxi vehicles | +1M trips per month
+200 fleet vehicles | +200 Bluetooth sensors | Maps
Maps | Traffic models | data facilitator
Satellite images | Reference traffic model

13. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Algorithmic Solutions: RoadTracer
● RoadTracer: Automatic Inference of Road Topology from Aerial Imagery
○ High-resolution aerial imagery is available for virtually all regions of the world
○ Inferring road topology from aerial imagery will significantly improve coverage

14. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Algorithmic Solutions: RoadTracer
● RoadTracer: Automatic Inference of Road Topology from Aerial Imagery
○ High-resolution aerial imagery is available for virtually all regions of the world
○ Inferring road topology from aerial imagery will significantly improve coverage
Not
trivial!

15. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Key Idea: Incremental Graph Construction (CVPR’18)
We train a convolutional neural network (CNN) to output the network one edge
(road segment) at a time.
CNN
[0.1, 0.9, 0.03, 0.01]
N E S W
Action: [Move, Stop]

16. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Algorithmic Solutions: Kharita & RoadRunner
● Kharita & RoadRunner: Precise Road Topology Inference from GPS
Trajectories
○ Crowdsourced GPS trajectories available for many cities
○ Can use to extract complex road topology very accurately
(highway interchanges, overpasses/underpasses, complex intersections)
Satellite Image OpenStreetMap
Hard
complex topologies,
overpasses/underpasses,
etc.

17. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Algorithmic Solution: RoadRunner
Focus on GPS traces
that went through the
yellow circles in
sequential order?
Satellite Image
GPS Histogram

18. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Algorithmic Solution: RoadRunner

19. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Automatic Map Inference in Action

20. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Robustness & Resilience
of Cities
How much can you take
before you fall down
How long does it take
you to stand up again

21. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
City Robustness 1/4
● 50+ cities from 6 continents (5 from GCC)
● Build their road networks from OSM shapefiles
● Simulate two types of failures
○ Random Attack: iteratively remove edges uniformly at random
○ Planned Attack: iteratively remove edges with high centrality
● Monitor failure thresholds

22. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
City Robustness 2/4
Doha
New YorkRiyadh

23. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
City Robustness 3/4
Random Attack Intentional Attack

24. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
City Robustness 4/4
Service Availability/Accessibility
● Assign each service (foursquare
location) to the nearest node in the
graph (iff dist <= 2km)
● Compute service availability in the
giant connected component before
and after failures

25. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
Other Projects
SmarTable
Zahma
Social Traffic
Monitoring

26. SmartCityAlgiers | Algiers June 27-28 2018 | Dr. Sofiane Abbar
QCRI is hiring for its new Center for Artificial
Intelligence (Q-CAI).
Come and talk to me!
Dr. Sofiane Abbar
(sabbar@qf.org.qa)
FYI