Slides from the talk given at MobileHCI 2015 in Copnehagen.

1. CommuniSense: Crowdsourcing Road
Hazards in Nairobi
Darshan Santani
Idiap Research Institute and EPFL (Switzerland)
Joint work with Jidraph Njuguna, Tierra Bills, Aisha W. Bryant, Reginald
Bryant, Jonathan Ledgard and Daniel Gatica-Perez
27 August 2015 | MobileHCI Copenhagen

3. Research Objective
Use of mobile crowdsourcing to gather road surface
quality information (potholes and speed-bumps) in
Nairobi

4. State of Transportation in Nairobi
● Modes of Transport
● Pedestrians (30-40% mode share)
● Matatus or private mini-buses – lifeline of Nairobians
● Taxis
● Boda Boda (motorcycles and bicycles)
Salon, Deborah, and Eric M. Aligula. "Urban travel in Nairobi, Kenya: analysis, insights, and opportunities." Journal of Transport
Geography, 2012

5. State of Transportation in Nairobi
● Modes of Transport
● Pedestrians (30-40% share)
● Matatus or private mini-buses – lifeline of Nairobians
● Taxis
● Boda Boda (motorcycles and bicycles)
● Lack of any form of road infrastructure monitoring
● Increase in road accidents and fatalities
Odero, W., Khayesi, M., & Heda, P. M. “Road traffic injuries in Kenya: magnitude, causes and status of intervention”. Injury
control and safety promotion, 2003

6. Research Contributions
Data
Verification
Real World
Deployment
Research
Intuition
Research
Challenges
Road Quality
Survey
Mobile
Application

7. Road Quality Survey

8. Road Quality Survey
● Objective: Status quo and willingness to participate
● Channels: Online (Google Forms) and SMS (mSurvey)
● Themes:
● Demographics
● Status Quo on Road Quality
● Overall Impact of Road Hazards
● Reporting Road Hazards
● Response: 880 responses (442 Online & 439 SMS)

9. Demographics
● Gender: Slightly biased towards male (Online – 62% M and SMS – 58% M)
● Age: Surveys cater to different age demographics
● SMS biased towards younger population (18–24 age group: 66%)
● Online biased towards relatively older segment (25–34 age group: 47%)

10. Demographics
● Gender: Slightly biased towards male (Online – 62% M and SMS – 58% M)
● Age: Surveys cater to different age demographics
● SMS respondents biased towards younger population (18–24 age group: 66%)
● Online respondents biased towards relatively older segment (25–34 age group: 47%)
● Residential Location: High-income neighborhoods represented more in Online
Online (N = 442) SMS (N = 439)

11. Status Quo on Road Quality
Road quality in residential
neighborhood
47% Online and 30% SMS
rated poor or very poor
Online
SMS
Potholes as a major
road nuisance
79% Online and 67% SMS
agreed or strongly agreed
Online
SMS

12. Impact of Road Hazards
77% considered road hazards to have a
major or severe impact on their vehicle’s
wear and tear.
Impact of road hazards on
personal travel discomfort
65% Online and 46% SMS
caused major or severe impact
Online
SMS

13. Reporting Road Hazards
● Do you know the process of reporting?
● No: 96% – Online and SMS – 77%
● How do you want to report?
● Mobile app: Online – 70% and SMS – 4%
● Do you own an Android-based phone?
● Yes: Online – 76% and SMS – 50%

14. User Comments (N = 101)
“Speed bumps are fine as long as they are marked so you don’t just “discover” them with your
head on the ceiling and stuff flying in the car. Look at the roads around the hospitals. I am
sure a patient is half killed before they even get to the hospital for treatment …”
“The state of our roads is dismal at best. Networks that were designed for a 90’s population
are being used, unchanged in the second decade of the 21st century”
“Road hazards is a major cause of road accidents in Kenya that should be addressed”
● Negligence of the local city council
● Personal commentary on the current state of traffic situation in Nairobi
● General praise for the survey
● Advice to improve status quo

15. Mobile Application
Data
Verification
Road Quality
Survey
Mobile
Application

16. CommuniSense
A mobile application to locate, describe, and photograph road hazards
Full Report Map It!

17. Field Study
● Days of deployment: 14 days
● Users: 30 university students
● Collected Data
● Full Reports – 101
● Map it! – 153
● Spatial Coverage
Full Reports (N = 99) Map It! (N = 109)

19. Field Study – Results
Severity of potholes Labeling of speed-bumps
55% encountered unlabeled
speed-bumps
57% rated moderate or higher

20. Lessons Learnt
● Backward Compatibility
● Target 2.3 instead of 4+ Android OS
● Cross device testing
● Not all devices (Huawei) handle the mapping well
● UI/UX matters

21. Lessons Learnt
● Backward Compatibility
● Target 2.3 instead of 4+ Android OS
● Cross device testing
● Not all devices (Huawei) handle the mapping well
● UI/UX matters
● Simple way to perform closed beta testing
● Feature Enhancements
● Upload photo from gallery

22. Data Verification
Data
Verification
Road Quality
Survey
Mobile
Application

23. Potential Malicious Behavior
Citizens Connect
Boston City Council
● Openness of entry –> malicious behavior
and sabotage
● Misreporting pervasive in crowdsourcing
● Verification is costly (!)
● MIT DARPA winning entry – 80% entries
malicious
J. C. Tang, M. Cebrian, N. A. Giacobe, H.-W. Kim, T. Kim, and D. B. Wickert. “Reflecting on the DARPA Red Balloon Challenge”.
CACM, 2011

24. Data Verification
Do people form consistent and reliable judgments describing
a road hazard based on its image?

25. Data Verification – Results
● Image Labeling: 92% of images verified with the same
labels as field users
● Hazard Attributes: 0.90 – 0.71 Intraclass correlation
Smooth Road (MTurk)
Speed Bump (Medium, Single, No)
Smooth Road (MTurk)
Speed Bump (Medium, Single, No)

26. Related Work
● Systems for reporting local civic issues
● Smartphone systems for developing countries
● Open Data Kit – https://opendatakit.org/
● Nokia (now Microsoft) Data Gathering –
https://www.microsoftdatagathering.net

27. Limitations
● Closing the loop, engaging local authorities in loop
● “And I do not trust that the city council would take our com-
plaints seriously.”
● “Actual or visible feedbacks would motivate me to report even
paying some costs.”
● “I would only report road issues if I thought something would be
done about it. I am not sure that’s currently the case.”
● Incentives to sustain active participation
● Spatial coverage – Matthew effect (rich gets richer)

28. Conclusions
Designed, implemented and tested a mobile
crowdsourcing platform which integrates crowd-
based verification for a world region that is still
under-represented and under-studied.

29. Q & A
Email: dsantani@idiap.ch
Twitter: @SabMayaHai
“The nice thing about potholes is there's a common enemy. Everyone hates it!”