communisense: crowdsourcing road hazards in nairobi
TRANSCRIPT
CommuniSense: Crowdsourcing Road Hazards in Nairobi
Darshan SantaniIdiap 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
Research Objective
Use of mobile crowdsourcing to gather road surface quality information (potholes and speed-bumps) in
Nairobi
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
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
Research Contributions
DataVerification
Real World Deployment
ResearchIntuition
ResearchChallenges
Road QualitySurvey
Mobile Application
Road Quality Survey
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)
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%)
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)
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
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
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%
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
Mobile Application
DataVerification
Road QualitySurvey
Mobile Application
CommuniSense
A mobile application to locate, describe, and photograph road hazards
Full Report Map It!
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)
Field Study – Results
Severity of potholes Labeling of speed-bumps
55% encountered unlabeled speed-bumps
57% rated moderate or higher
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
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
Data Verification
DataVerification
Road QualitySurvey
Mobile Application
Potential Malicious Behavior
Citizens ConnectBoston 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
Data Verification
Do people form consistent and reliable judgments describing a road hazard based on its image?
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)
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
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)
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.
Q & A
Email: [email protected]: @SabMayaHai
“The nice thing about potholes is there's a common enemy. Everyone hates it!”