Crowdsourcing de données mobiles

1. Crowd-sensing made easy!
ADAM project-team
Université Lille 1 – LIFL
Inria Lille – Nord Europe
Christophe Ribeiro
1
jeudi 25 avril 13

2. Why do we collect data?
• Better understanding of crowd
behavior and its environment
– E.g., optimizing public transport services
2
www.apisense.fr
jeudi 25 avril 13

3. Why do we collect data?
• Better understanding of crowd
behavior and its environment
– E.g., optimizing public transport services
2
Road map of Chicago
www.apisense.fr
jeudi 25 avril 13

4. Why do we collect data?
• Better understanding of crowd
behavior and its environment
– E.g., optimizing public transport services
2
Paths of Chigago TwitteresRoad map of Chicago
www.apisense.fr
jeudi 25 avril 13

5. Mobile|Phone Sensing
• Revolution driven by smart devices to
collect of crowd activity traces
34
www.apisense.fr
jeudi 25 avril 13

6. Mobile|Phone Sensing
• Revolution driven by smart devices to
collect of crowd activity traces
34
Increasing popularity
www.apisense.fr
jeudi 25 avril 13

7. Mobile|Phone Sensing
• Revolution driven by smart devices to
collect of crowd activity traces
34
www.apisense.fr
jeudi 25 avril 13

8. Mobile|Phone Sensing
• Revolution driven by smart devices to
collect of crowd activity traces
34
App distribution
channels
www.apisense.fr
jeudi 25 avril 13

9. Mobile|Phone Sensing
• Revolution driven by smart devices to
collect of crowd activity traces
34
www.apisense.fr
jeudi 25 avril 13

10. Mobile|Phone Sensing
• Revolution driven by smart devices to
collect of crowd activity traces
34
GPS
WIFI/3G/4G
Accelerometer
Compas
CameraMicrophone
Rich suites of sensors
www.apisense.fr
jeudi 25 avril 13

11. Mobile|Phone Sensing
• Revolution driven by smart devices to
collect of crowd activity traces
34
www.apisense.fr
jeudi 25 avril 13

12. Crowd-sensing
• Capability of lifting a (large) diffuse
group of participants to delegate the
task of retrieving trustable data from
the field
4
GPS
WIFI/3G/4G
Accelerometer
Compas
CameraMicrophone
Crowd + Sensing
www.apisense.fr
jeudi 25 avril 13

13. Challenges summary
5
Task
description
Task
execution
Worker
recruitment
Task
deployment
Data upload
Worker
rewarding
Crosscutting
challenges
Privacy Energy
Software
challenges Scalability SecurityFlexibility
Hot topics Motivation Incentives
www.apisense.fr
jeudi 25 avril 13

14. Multi-Cloud Platform
6
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jeudi 25 avril 13

15. Multi-Cloud Platform
6
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jeudi 25 avril 13

16. Multi-Cloud Platform
6
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jeudi 25 avril 13

17. Multi-Cloud Platform
6
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jeudi 25 avril 13

18. Multi-Cloud Platform
6
www.apisense.fr
jeudi 25 avril 13

19. Central Node
• A trustable central server
– Intermediary between collector node &
workers
– Guarantees workers anonymity (generated
ids)
– Checks the task scripts and rewards
workers
• Cloud-oriented data storage
–
7
Scalability
Privacy
www.apisense.fr
jeudi 25 avril 13

20. Crowdsensing
• Mobile application
– Downloads & executes scripts (sandbox)
– Uploads datasets when plugged
– Controls sensor privileges & privacy filters
8
Time filter
Sensors
privileges
Location filter
Energy
Privacy
jeudi 25 avril 13

21. GSM Signal Open Map
9
trace.setHeader(’gsm_operator’, gsm.operator());
location.onLocationChanged({
period: ’5min’,
distance: ’10m’
}, function (loc) {
return trace.add({
time: loc.timestamp,
lat: loc.latitude,
lon: loc.longitude,
wifi: {
network_id: wifi.bssid(),
signal_strength: wifi.rssi()
},
gsm: {
cell_id: gsm.cellId(),
signal_strength: gsm.dbm()
}
});
});
jeudi 25 avril 13

22. GSM Signal Open Map
9
trace.setHeader(’gsm_operator’, gsm.operator());
location.onLocationChanged({
period: ’5min’,
distance: ’10m’
}, function (loc) {
return trace.add({
time: loc.timestamp,
lat: loc.latitude,
lon: loc.longitude,
wifi: {
network_id: wifi.bssid(),
signal_strength: wifi.rssi()
},
gsm: {
cell_id: gsm.cellId(),
signal_strength: gsm.dbm()
}
});
});
jeudi 25 avril 13

23. GSM Signal Open Map
9
trace.setHeader(’gsm_operator’, gsm.operator());
location.onLocationChanged({
period: ’5min’,
distance: ’10m’
}, function (loc) {
return trace.add({
time: loc.timestamp,
lat: loc.latitude,
lon: loc.longitude,
wifi: {
network_id: wifi.bssid(),
signal_strength: wifi.rssi()
},
gsm: {
cell_id: gsm.cellId(),
signal_strength: gsm.dbm()
}
});
});
Ground
truth
Open
map
jeudi 25 avril 13

24. Collecting exceptions in the
wild
10
logcat.onLog {filter: ’*:E’},
(log) -> if log.message contains ’Exception’
trace.save
message: log.message,
time: log.timestamp,
application: apps.process(log.pid).applicationName,
topTask: apps.topTask().applicationName
www.apisense.fr
jeudi 25 avril 13

25. Collecting exceptions in the
wild
10
logcat.onLog {filter: ’*:E’},
(log) -> if log.message contains ’Exception’
trace.save
message: log.message,
time: log.timestamp,
application: apps.process(log.pid).applicationName,
topTask: apps.topTask().applicationName
www.apisense.fr
jeudi 25 avril 13

26. Mobility model
11
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jeudi 25 avril 13

27. 70 %
30 %
100 %
100 %
Mobility model
11
www.apisense.fr
jeudi 25 avril 13

28. 70 %
30 %
100 %
100 %
Mobility model
11
Home
Work
???
www.apisense.fr
jeudi 25 avril 13

29. 70 %
30 %
100 %
100 %
Mobility model
11
Home
Work
???
Parvis Saint-Maurice
avenue Halley
2 Place de Béthune
www.apisense.fr
jeudi 25 avril 13

30. Inria Lille
Bistro
70 %
30 %
100 %
100 %
Mobility model
11
Home
Work
???
Parvis Saint-Maurice
avenue Halley
2 Place de Béthune
www.apisense.fr
jeudi 25 avril 13

31. 12
Christophe.Ribeiro@inria.fr
Nicolas HADERER
Romain ROUVOY
Lionel SEINTURIER
Questions ?
www.apisense.fr
jeudi 25 avril 13