mobile crowdsourcing: challenges and applications

Dagstuhl Seminar 10042, Demetris Zeinalipour, University of Cyprus, 26/1/2010

7th Webdatanet MC, WG, TF Meetings, Workshops & Conference on Mobile Research, Larnaca, Cyprus, March 31st, 2014.

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/


© Demetrios Zeinalipour-Yazti, Webdatanet, 31/3/14, http://dmsl.cs.ucy.ac.cy/

2/32

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", Georgios Chatzimilioudis and

Demetrios Zeinalipour-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”, 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.



3/32

CrowdsourcingOpen Call (Task)

Solutions

RewardsAssigner

(Crowdsourcer)

Contributors(Solvers)

Platform

Could capture a mobile web survey posted by Assigner to Contributors through a Platform for monetary or ethical benefit.



4/32

Web CrowdsourcingMicrotasking Platform:

a) Reward

Qualifications

b) Redundancy: Each worker solves a Hit once (3-5 assignment per hit) to enable majority voting



5/32

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



6/32

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.



7/32

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.



8/32

Declarative Crowdsourcing• CrowdDB, Qurk, Deco, MoDaS, Crowdforge.

Crowd Extensions

CrowdDB: Answering Queries with Crowdsourcing,M. J. Franklin, D. Kossmann ,T. Kraska, S. Ramesh, R. Xin, SIGMOD‘11 & VLDB'11Demo

SELECT abstract FROM talkWHERE title = "CrowdDB";



9/32

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).

txteagle: Mobile Crowdsourcing, Internationalization, Design and Global Development, LNCS Volume 5623, pp 447-456, 2009.

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, ..



10/32

Smartphone CrowdsourcingApril 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



11/32

• A smartphone crowd is constantly moving and sensing providing large amounts of opportunistic data enabling new applications

Crowdsourcing with Smartphones

• “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.



12/32

Smartphone Crowdsourcing: Challenges

Challenges (Beyond Web Crowdsourcing)1. Big Data

– Velocity by sensor data generates Volume

2. 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?

3. (Location) Privacy– Coarse-grain (cell, wifi) vs. fine (gps)

4. Energy Consumption– Power Hungry (GPS, Brightness, etc.)



13/32

Smartphone Crowdsourcing: Challenges

Challenges (Beyond Web Crowdsourcing)5. Calibration and Multi-device Issues

– Different readings by different sensors (e.g., Wifi RSS, magnetic field, etc.)

– Incomplete Data & Quality Issues.

6. Connectivity Issues– Workforce might have intermittent connectivity (e.g.,

while travelling) thus can’t provide online readings.

7. Heterogeneous Clients hinders deployment– Different OSes, sensor, features, APIs, etc. – One supports active background tasks another OS

doesn’t, etc.



14/32

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



15/32

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.



16/32

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



17/32

Urban Location Data

Viewer, Widget

Navigator

Anyplace Architecture



18/32

Urban Location Data

http://anyplace.cs.ucy.ac.cy/

Live Demo!

• Anyplace Indoor Information Service (IIS)



19/32

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)



20/32

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.



21/32

Talk Outline




• Mobile Crowdsourcing Testbeds– SmartLab Smartphone Programming Cloud



22/32

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!



23/32


• 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/



24/32


• Rayzit User Map



25/32


• 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)



26/32

Talk Outline




• Urban Sensing Testbeds– SmartLab Smartphone Programming Cloud



27/32

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),



28/32

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



29/32

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.



30/32

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



31/32

Urban Sensing Testbeds

Rent

See/Click

Shell

File Sys.

Automation

Debug

Data

Manage

SmartLab (http://smartlab.cs.ucy.ac.cy/)

Live Demo!



32/32

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 …


7th Webdatanet MC, WG, TF Meetings, Workshops & Conference on Mobile Research, Larnaca, Cyprus, March 31st, 2014.

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?

mobile crowdsourcing: challenges and applications

Documents