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CommuniSense: Crowdsourcing Road Hazards in Nairobi

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Slides from the talk given at MobileHCI 2015 in Copnehagen.

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CommuniSense: Crowdsourcing Road Hazards in Nairobi

  1. 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
  2. 2. Research Objective Use of mobile crowdsourcing to gather road surface quality information (potholes and speed-bumps) in Nairobi
  3. 3. 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
  4. 4. 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
  5. 5. Research Contributions Data Verification Real World Deployment Research Intuition Research Challenges Road Quality Survey Mobile Application
  6. 6. Road Quality Survey
  7. 7. 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)
  8. 8. 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%)
  9. 9. 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)
  10. 10. 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
  11. 11. 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
  12. 12. 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%
  13. 13. 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
  14. 14. Mobile Application Data Verification Road Quality Survey Mobile Application
  15. 15. CommuniSense A mobile application to locate, describe, and photograph road hazards Full Report Map It!
  16. 16. 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)
  17. 17. Field Study – Results Severity of potholes Labeling of speed-bumps 55% encountered unlabeled speed-bumps 57% rated moderate or higher
  18. 18. 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
  19. 19. 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
  20. 20. Data Verification Data Verification Road Quality Survey Mobile Application
  21. 21. 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
  22. 22. Data Verification Do people form consistent and reliable judgments describing a road hazard based on its image?
  23. 23. 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)
  24. 24. 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
  25. 25. 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)
  26. 26. 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.
  27. 27. Q & A Email: dsantani@idiap.ch Twitter: @SabMayaHai “The nice thing about potholes is there's a common enemy. Everyone hates it!”

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