CROWD-SENSING/SOURCINGMirko Presser @mirkopresserVice President of the IoT ForumHead of Research and InnovationSmart City LabAlexandra Instituttet A/S

THE WISDOM OF CROWDS

The crowd at a county fair accurately guessed the weight of an ox when their individual guesses were averaged (the average was closer to the ox's true butchered weight than the estimates of most crowd members, and also closer than any of the separate estimates made by cattle experts).

- the wisdom of crowds

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Read more about taxonomy here: Hosseini, M.; Phalp, K.; Taylor, J.; Ali, R., "The four pillars of crowdsourcing: A reference model," in Research Challenges in Information Science (RCIS), 2014 IEEE Eighth International Conference on , vol., no., pp.1-12, 28-30 May 2014

THE KEY COMPONENTS

1. An organisation that has a task it needs performed

2. A community (crowd) that is willing to perform the task

3. An online environment that allows the work to take place and the community to interact with the organization

4. Mutual benefit for the organization and the community

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CROWD/SOURCING DEFINITION

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crowd organisation

crowdsourcing

market surveynew M&M colour

opensourcewikipedia

“CLASSICAL” EXAMPLES

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CROWDSOURCING BY TYPE

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Type How it works Kinds of problems ExamplesKnowledge discovery and management

Organization tasks a crowd with finding and collecting information into a common location and format

Ideal for info gathering, organization and reporting problems, such as the creation of collective resources

Peer-to-patent SeeClickFix

Broadcast search Organization tasks a crowd with solving empirical problems

Ideal for ideation problems with empirical provable solutions, such as scientific problems

InnoCentive

Goldcorp Challenge

Peer-vetted creative production

Organization tasks a crowd with creating and selecting creative ideas

Ideal for ideation problems where solutions are matters of taste or market support, such as design or aesthetic problems

Threadless

Doritos Crash the Super Bowl Contest

Next Stop Design

Distributed human-intelligence tasking

Organization tasks a crowd with analyzing large amounts of information

Ideal for large-scale data analysis where human intelligence is more efficient or effective than computer analysis

Amazon Mechanica

Subvert and Profit

FROM CROW/SENSING TO SOURCING

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Criterion Involvement of the user Type of measurement

Types of crowd/sensing

• Participatory crowd/sensing (active)

• Opportunistic crowd/sensing (passive)

• Environmental (pollution)

• Infrastructure (traffic)

• Social (cinema visit)

Knowledge discovery and management

FUKUSHIMA: SAFECAST

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https://vimeo.com/113486504

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SMARTSANTANDER: PSENS

https://www.youtube.com/watch?v=E6mqiSc-8ls

ECOSENSE: TRANSPORT MODE

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https://vimeo.com/56018056

INGRESS

Ryoma Kawajiri, Masamichi Shimosaka, and Hisashi Kashima. 2014. Steered crowdsensing: incentive design towards quality-oriented place-centric crowdsensing. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp '14). ACM, New York, NY, USA, 691-701. DOI=http://dx.doi.org/10.1145/2632048.2636064

https://www.youtube.com/watch?v=92rYjlxqypM

INGRESS – NP-HARD

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ISSUES WITH CROWD/SENSING

• Motivating and maintaining the crowd– intrinsic motivators (fun and challenge)– extrinsic motivators (financial reward, fame, social pressure)– which motivators generate higher quality of work?

• Technology– data collection mechanisms (low power, low cost)– reliability, quality and frequency of data – data analytics and annotation– engagement – the fun-factor

• Ethics, Legal, Ownership and Copyright

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Mirko Presser @mirkopresserVice President of the IoT ForumHead of Research and InnovationSmart City LabAlexandra Instituttet A/S