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Mobile Crowdsourcing: Challenges and Applications

Mobile Crowdsourcing: Challenges and Applications. Demetrios Zeinalipour-Yazti Data Management Systems Laboratory Department of Computer Science University of Cyprus http://dmsl.cs.ucy.ac.cy/. 7th Webdatanet MC, WG, TF Meetings, Workshops & Conference on

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Mobile Crowdsourcing: Challenges and Applications

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  1. Mobile Crowdsourcing: Challenges and Applications Demetrios Zeinalipour-Yazti Data Management Systems Laboratory Department of Computer Science University of Cyprus http://dmsl.cs.ucy.ac.cy/ 7th Webdatanet MC, WG, TF Meetings, Workshops & Conference on Mobile Research, Larnaca, Cyprus, March 31st, 2014.

  2. Talk Objective • To review primitive crowdsourcing concepts and challenges. • To show how these challenges emerge and evolve in Mobile environments. • To present some of our own developments related to: Location Data, Crowd Micro-blogging, Testbeds. • Much of the discussion is work in progress. • References: • "Crowdsourcing for Mobile Data Management", GeorgiosChatzimilioudis and DemetriosZeinalipour-Yazti, Proceedings of the 14th IEEE International Conference on Mobile Data Management (IEEE MDM '13), Milan Italy, Volume 2, pp. 3-4, 2013. • “Crowdsourcing with Smartphones”, GeorgiosChatzimiloudis, Andreas Konstantinidis, Christos Laoudias, DemetriosZeinalipour-Yazti, IEEE Internet Computing, Special Issue: Sep/Oct 2012 - Crowdsourcing, May 2012. IEEE Press, Volume 16, pp. 36-44, 2012.

  3. Crowdsourcing Open Call (Task) Solutions Assigner (Crowdsourcer) Rewards Contributors (Solvers) Platform • Could capture a mobile web survey posted by Assigner to Contributors through a Platform for monetary or ethical benefit.

  4. Web Crowdsourcing Microtasking Platform: Qualifications b) Redundancy: Each worker solves a Hit once (3-5 assignment per hit) to enable majority voting a) Reward

  5. Web Crowdsourcing: Incentives • Tangible (Monetary) Incentives • Cash, Credit or Gifts (MTurk, Kickstarter) • Unintended or as-a-by-product (reCaptchas) • Ethical Incentives • Socialize & Fun • Earn Prestige • Altruism • Learn something New • Usually a combination of several incentives

  6. Web Crowdsourcing: Challenges • How to Recruit Contributors (randomly, marketplaces?) / What the Contributors Can Do (qualifications, tests)? • How to Combine their Contributions? • How to Manage Abuse? • How To Scale/Manage Complex/Larger Tasks? • Openness / Quality? • Disclosure Issues (Privacy related to Tasks, NDAs?) • Minimum Wages & Social Contributions? Anhai Doan, Raghu Ramakrishnan, and Alon Y. Halevy. 2011. Crowdsourcing systems on the World-Wide Web. Commun. ACM 54, 4 (April 2011), 86-96.

  7. Web Crowdsourcing: Challenges • How to Recruit Contributors (randomly, marketplaces?) / What the Contributors Can Do (qualifications, tests)? • How to Combine their Contributions? • How to Manage Abuse? • How To Scale/Manage Complex/Larger Tasks? • Openness / Quality? • Disclosure Issues (Privacy related to Tasks, NDAs?) • Minimum Wages & Social Contributions? Anhai Doan, Raghu Ramakrishnan, and Alon Y. Halevy. 2011. Crowdsourcing systems on the World-Wide Web. Commun. ACM 54, 4 (April 2011), 86-96.

  8. Declarative Crowdsourcing • CrowdDB, Qurk, Deco, MoDaS, Crowdforge. • SELECT abstract • FROM talk • WHERE title = "CrowdDB"; Crowd Extensions CrowdDB: Answering Queries with Crowdsourcing,M. J. Franklin, D. Kossmann ,T. Kraska, S. Ramesh, R. Xin, SIGMOD‘11 & VLDB'11Demo

  9. Mobile Crowdsourcing • txtEagle (now JANA) founded by Nathan Eagle (PhD, MIT, 2005) a first-of-a-kind mobile CS system: • Requesters: can assign small tasks (translation, transcription and surveys) on their mobile phones. • Workers (today 3.48 Billion Workers in 102 countries!): : rewarded with airtime on their mobile subscriber accounts or MPESA (mobile money described next). • Other Tasks: • Blood Bank: to report blood levels of local hospitals centrally by nurses. • Software Localization: 60 local dialects in Kenya • Citizen Journalism, Sentiment Analysis, Surveys, .. txteagle: Mobile Crowdsourcing, Internationalization, Design and Global Development, LNCS Volume 5623, pp 447-456, 2009.

  10. Smartphone Crowdsourcing April 2013: Beginning of Smartphone Era! • IDC (April, 2013):Smartphone sales exceeded feature phone sales. • 51.6% were Smartphones (216M units) • 48.4% were Feature Phones (186M units) • The bulk of mobile phones are acquired in the developing world (e.g., China, India, Africa etc.) • Smartphones = Unlimited Sensors: • GPS, Accelerometer, Compass, Orientation, Temperature, Light, Proximity, Pressure, Elevation, … • New Opportunities for Crowdsourcing with Sensors More Smartphones Were Shipped in Q1 2013 Than Feature Phones, An Industry First According to IDC, 25 Apr 2013, http://www.idc.com/getdoc.jsp?containerId=prUS24085413

  11. Crowdsourcing with Smartphones • A smartphone crowd is constantly moving and sensing providing large amounts of opportunistic data enabling new applications • “Crowdsourcing with Smartphones”, Georgios Chatzimiloudis, Andreas Konstantinidis, Christos Laoudias, Demetrios Zeinalipour-Yazti, IEEE Internet Computing, Special Issue: Sep/Oct 2012 - Crowdsourcing, May 2012. IEEE Press, Volume 16, pp. 36-44, 2012.

  12. Smartphone Crowdsourcing: Challenges Challenges (Beyond Web Crowdsourcing) • Big Data • Velocity by sensor data generates Volume • Typing and User Interfaces • Participatory typing is cumbersome due to small form factor / display keyboard. • Scrolling & Crowded GUIs. Attention issues due to possible mobility. Opportunistic Solutions? • (Location) Privacy • Coarse-grain (cell, wifi) vs. fine (gps) • Energy Consumption • Power Hungry (GPS, Brightness, etc.)

  13. Smartphone Crowdsourcing: Challenges Challenges (Beyond Web Crowdsourcing) • Calibration and Multi-device Issues • Different readings by different sensors (e.g., Wifi RSS, magnetic field, etc.) • Incomplete Data & Quality Issues. • Connectivity Issues • Workforce might have intermittent connectivity (e.g., while travelling) thus can’t provide online readings. • Heterogeneous Clients hinders deployment • Different OSes, sensor, features, APIs, etc. • One supports active background tasks another OS doesn’t, etc.

  14. Talk Outline • Introduction & Challenges • Location Data Crowdsourcing • Anyplace Indoor Information System • Crowd Micro-blogging • Rayzit Crowd Messaging Service • Mobile Crowdsourcing Testbeds • SmartLab Smartphone Programming Cloud

  15. Urban Location Data • People spend 80-90% of their time inside buildings, while 70% of cellular calls and 80% of data connections originate from indoors. • GPS has low availability indoors due to the blockage or attenuation of the satellite signals but it is also very power hungry. • Smartphones can nowadays localize off-the-shelf with onboard sensors and WiFi signal fingerprints (coined Hybrid Localization) • New Applications: • In-building Navigation (Malls, Airports, Museums, Schools, etc.) • Asset Tracking and Inventory Management (Hospitals, etc) • Elderly support for Ambient and Assisted Living (AAL) • Augmented Reality (Firefighters), Social Networking, etc.

  16. Urban Location Data • References • [Airplace] "The Airplace Indoor Positioning Platform for Android Smartphones", C. Laoudias et. al., Best Demo Award at IEEE MDM'12. (Open Source!) • [HybridCywee] "Demo: the airplace indoor positioning platform", C.-L. Li, C. Laoudias, G. Larkou, Y.-K. Tsai, D. Zeinalipour-Yazti and C. G. Panayiotou, in ACM Mobisys'13. Video at: http://youtu.be/DyvQLSuI00I • [UcyCywee] IPSN’14 Indoor Localization Competition (Microsoft Research), Berlin, Germany, April 13-14, 2014. • [Anyplace] Crowdsourced Indoor Localization and Navigation with Anyplace, In ACM/IEEE IPSN’14. http://anyplace.cs.ucy.ac.cy/ Cywee / Airplace

  17. Urban Location Data Anyplace Architecture Navigator Viewer, Widget

  18. Urban Location Data • Anyplace Indoor Information Service (IIS) http://anyplace.cs.ucy.ac.cy/ Live Demo!

  19. Anyplace Crowdsourcing Challenges • A) Big Data • Massively process RSS log traces to generate a valuable Radiomap • Utilized for KNN positioning • Processing current logs in Anyplace for a single building might take several minutes! • Challenges in MapReduce: • Spatio-temporal Analysis • Missing Values / Outliers / Quality / Multi-device Issues (see next)

  20. Anyplace Crowdsourcing Challenges • B) Quality: Unreliable Crowdsourcers, Multi-device Issues, Hardwar Outliers, Temporal Decay, etc. • Remark: There is a Linear Relation between RSS values of devices. • Challenge: Can we exploit this to align reported RSS values? "Crowdsourced Indoor Localization for Diverse Devices through Radiomap Fusion", C. Laoudias, D. Zeinalipour-Yazti and C. G. Panayiotou, "Proceedings of the 4th Intl. Conference on Indoor Positioning and Indoor Navigation" (IPIN '13), Montbeliard-Belfort France, 2013.

  21. Talk Outline • Introduction & Challenges • Location Data Crowdsourcing • Anyplace Indoor Information System • Crowd Micro-blogging • Rayzit Crowd Messaging Service • Mobile Crowdsourcing Testbeds • SmartLab Smartphone Programming Cloud

  22. Crowd Micro-blogging • Social Media (Facebook, Linked-in, … ) utilize a Social Graph (friendship, follower, followee) to map the relationships between users. • Social Media in Urban Settings: Issues • Urban Applications many times require location-based rather than social-based interactions, e.g., • Inform my neighboring drivers about an accident (e.g., in Waze). • Inform people in a city about an event. • Location-based services suffer from bootstrapping • e.g., Check in to Foursquare and find nobody else there • Interacting with the Crowd, calls for stronger Privacy!

  23. Crowd Micro-blogging • We developed Rayzit for Windows Phone after receiving an Industrial Award by the Appcampus Program (Microsoft, Nokia & Aalto, Finland). • Ranked among the 5 best apps of the given program among 3500 submissions. • A few thousand downloads and active users on our big-data backend. http://rayzit.com/

  24. Crowd Micro-blogging • Rayzit User Map

  25. Crowd Micro-blogging • Topics: Location, Surveys,Thoughs, Feelings • Most answered rayz (responses) • “Rain! Lovely.” (228) • “Any good PGs near Avanshi RoadCBE?” (142) • “Which windows phone do you have?” (119) • “anyone around..???” (94) • “Share a secret ..” (90) • “Rayzit: What is the next feature you would like to see?” (81) • “I love.... (continue)” (58) • “Where are you from? I want to test Rayzit's location algorithms.” (52) • “Where to dine in Coimbatore if you want to have a dinner peacefully and by yourself?” (40)

  26. Talk Outline • Introduction & Challenges • Location Data Crowdsourcing • Anyplace Indoor Information System • Crowd Micro-blogging • Rayzit Crowd Messaging Service • Urban Sensing Testbeds • SmartLab Smartphone Programming Cloud

  27. Urban Sensing • "People sense and contribute data about their surroundings using mobile devices" • Dartmouth | Metrosense: SoundSense, CenceMe, Sensor Sharing, BikeNet, AnonySense, and Second Life Sensor. • MIT | Cartel: VTrack/CTrack, PotHole • Harvard : Citysense (grew out of MoteLab) • UNSW: Noise (Earphone) & Air pollution (HazeWatch, CommonSense),

  28. Urban Sensing • This kind of a paradigm has nowadays an industrial success. • CrowdSensing app by Waze (Israel) now Google! • Waze: Free GPS Navigation with Turn by Turn • Workers report their GPS location and events (gas prices, traffic jams, etc.) • Real-time updates to users

  29. Urban Sensing Testbeds • Smartphone Testbeds: Allow the requestor to deploy a task (app, data collection, remote terminal etc.) directly on the end smartphone devices. • [PRISM] T. Das, P. Mohan, V.N. Padmanabhan, R. Ramjee, and A. Sharma, “PRISM: Platform for Remote Sensing using Smartphones”, In ACM MobiSys’10. • [CrowdLab] E. Cuervo, P. Gilbert, B. Wu, and L.P. Cox, “CrowdLab: An Architecture for Volunteer Mobile Testbeds”, In COMSNETS’11. • [PhoneLab] G. Challen et. al. “PhoneLab: A Large-Scale Participatory Smartphone Testbed”, In USENIX NSDI’12 (poster). • [SmartLabDemo] "Demo: a programming cloud of smartphones", A. Konstantinidis, C. Costa, G. Larkou, D. Zeinalipour-Yazti, In ACM Mobisys '12. • [SmartLab] "Managing Smartphone Testbeds with SmartLab", G. Larkou, C. Costa, P. Andreou, A. Konstantinidis, D. Zeinalipour-Yazti, In 27th USENIX LISA '13, Washington D.C. USA, 115-132, 2013.

  30. Urban Sensing Testbeds • We developed a comprehensive architecture for managing smartphones through a web browser. • SmartLab (http://smartlab.cs.ucy.ac.cy/): • 40+ Android Devices, Real Sensors, Real Computing Stack • Different Connection Modalities: 3G (unlimited 3G bancwidth by MTN Telecom), Wifi, Wired, Remote  Static Androids Mobile Androids

  31. Urban Sensing Testbeds SmartLab (http://smartlab.cs.ucy.ac.cy/) Rent Manage See/Click Shell File Sys. Automation Debug Data Live Demo!

  32. Urban Sensing Testbeds Data Collection in Smart Cities • How to handle a fleet of Android-powered entertainment equipment installed on 100 buses? • How to manage a city-scale infrastructure comprising of low-power, low-value Android-oriented devices? • How to manage a city-scale SETI-like computational cluster comprising of Smartphones. • We tend to change smartphones faster than PCs …

  33. Mobile Crowdsourcing: Challenges and Applications Demetrios Zeinalipour-Yazti Data Management Systems Laboratory Department of Computer Science University of Cyprus http://dmsl.cs.ucy.ac.cy/ Thanks! Questions? 7th Webdatanet MC, WG, TF Meetings, Workshops & Conference on Mobile Research, Larnaca, Cyprus, March 31st, 2014.

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