The research team from TU Delft and DAT.Mobility worked on intelligently fusing data about pedestrian flows from different types of sensors (wifi, gps, counting cameras) to estimate crowd densities, travel speeds and flows at different routes of SAIL. Besides that, open social media platforms were crawled and analysed to get insight in demographics of the crowd and crowd sentiments at different hotspots of SAIL during the event. The collected data and state estimates can be used for more advanced and efficient crowd management support in the future. At SAIL 2015 we really focused on testing new sensor technologies, crowd data algorithms and analytics and assess whether they can be made useful and are reliable. This should give us insight in how we can improve crowd management of large events in cities in the future and provide visitors and citizens a more pleasurable experience.

1. SAIL 2015
1 Week, >1.5M Visitors, 300K/Day
Largest public sailing event in the World
Mix of Commuters /
Tourists / Visitors
Main Route: ~ 6Km
ORGANIZERS’
GOAL:
Real-time crowd
monitoring
How many people are in
my area?
What kind of people are
these?
Where do they come from?
Which routes do they use?
How long do they stay in
my area and for what
purpose?
What are travel times on
these routes?
What measures can I apply
to manage the crowd?
What is the effect of such
measures?

2. SAIL Crowd
Monitoring Dashboard
Cameras count
pedestrians (2 ways)
Wifi sensors follow
Smartphones from
sensor to sensor
Some visitors are
equipped with GPS
trackers
Social Media data (social-media activity by area, properties of visitors)
Moreover…
- Camera verification in
location with high
expected crowd
- Aerial pictures
Mark Hünneman, Serge Hoogendoorn, Winnie Daamen
Dorine Duives, Yufei Yuan, Stefano Bocconi, Christiaan Titos Bolivar

3. SAIL 2015
8 Cameras
Count heads@Location
High Precision,
No Semantics
Low Density
0
2000
4000
6000
8000
10000
12000
6 11 16
In Out Total

4. SAIL 2015
20 WiFI
Fixed Position
No Semantics
Low Density
Count Devices@Location

5. SAIL 2015
100 GPS
Random
Distribution,
Precise Semantics
(Demographic,
Usage Role)
Low Density
Track Route

6. Social Glass
Real-time Analytics
Crowd Dashboard
Flow and route choice
Densities (#/m2)
Speeds and durations
Geo-location mapping
Visitors demographics
City role

7. SAIL 2015
Research Goal:
Analysis and validation of mobility patterns as observed from social data
Social Media
Count Users,
Track Routes
Biased Distribution
Inferred Semantics
(Demographic, Usage
Role, Topic,
Sentiment)
Higher Density

8. SocialMedia Vs. WiFi Vs. CameraSocial Media
Camera
WiFi

9. SocialMedia Vs. GPS

10. Research Goal:
Analysis and validation of mobility patterns as observed from
social data

11. Residents Foreign Tourists Dutch TouristsInstagram. Geo-located posts related to SAIL 2015
Social Media Activities

12. Druk
Vol
Gedrang
Bomvol
Boordevol
Afgeladen
Volgepakt
Crowded
Busy
Jam
Jam-packed
ForeignTouristsResidents
Instagram. Geo-located posts related to SAIL 2015
“Crowdedness"