1. Crowdsourcing and
smartphone technology
Luigi Ceccaroni, Senior member of research staff
Blue Photonics 2013, Texel (NL), March 18, 2013

2. Introduction
• Citizens as environmental data consumers
• Monitoring tackled by scientists or policy makers alone
• Expensive
• Hard to use technology
• Quantity, coverage?
• High quality
• Sustainable?
• Citizens as environmental data creators and consumers
• Monitoring tackled by scientists, policy makers and citizens
• Low cost
• Easy to use technology
• Quantity, coverage?
• Quality?
• Sustainable
Luigi Ceccaroni - Crowdsourcing and smartphone technology

3. The convergence of two trends
• The proliferation of cheap, powerful sensors
• Commonplace objects understanding what we do with them
Luigi Ceccaroni - Crowdsourcing and smartphone technology

4. The convergence of two trends
• The proliferation of cheap, powerful sensors
• Commonplace objects understanding what we do with them
• Our personal identities firmly connected to our profiles on
social networks
Luigi Ceccaroni - Crowdsourcing and smartphone technology

5. Interaction made “social”
• How to create peer pressure?
• Recycle and impress your (Facebook) friends, or don't recycle
and risk incurring their wrath
• Share your weight with your Twitter followers; it will help you
to stick to a diet
• Monitor the environment and impress your friends, or don't
monitor the environment and…???
• Like a videogame, with points for doing good?
• Why create peer pressure?
• We are not mere automatons who assist big data in asking
and answering questions. Well, we shouldn’t be…

6. The social-engineering context
• Social engineering disguised as product engineering
• From smart cars to smart sensors, "smart" as the shorthand
for transforming present-day social reality
• Smart technologies becoming more intrusive
• Risk of undermining our autonomy by supporting behaviors
that someone somewhere has deemed desirable:
• Smart forks informing us that we are eating too fast
• Smart toothbrushes urging us to spend more time brushing our
teeth
• Smart sensors in our cars telling us we drive too fast
• Smartphones telling us which beach is better for us
• Devices giving us useful feedback
• But also sharing everything they know about our habits with
institutions whose interests may be different from our own

7. The social-engineering context

8. “Good smart" and "bad smart"
• “Good smart“: Devices leaving us in complete control of
the situation and seek to enhance our decision-making by
providing more information:
• An Internet-jacked kettle alerting us when the national power
grid is overloaded
• Not preventing us from boiling yet another cup of tea, but adding
an extra ethical dimension to that choice
• A grocery cart scanning the bar codes of products we put into
it, informing us of their nutritional benefits and country of origin
• Enhancing—rather than impoverishing—our autonomy
• An application to contribute to ocean-color research, coupling
color to the most important life form in the water, the
phytoplankton, and informing about the ocean’s health
• What’s in it for me? Education, pollution, sediments…
• Is it sustainable? Public, private, artists…

9. “Good smart" and "bad smart"
• “Bad smart“: Technologies making certain choices and
behaviors impossible; smart gadgets seeking to limit, not to
expand, what we can do:
• Facial recognition technologies confirming we are who we say
we are…
• We must resist attempts to universalize this logic:

10. “Good smart" and "bad smart"
• “Bad smart“: Technologies making certain choices and
behaviors impossible; smart gadgets seeking to limit, not to
expand, what we can do:
• Facial recognition technologies confirming we are who we say
we are…
• We must resist attempts to universalize this logic:

11. “Good smart" and "bad smart"
• “Bad smart“: Technologies making certain choices and
behaviors impossible; smart gadgets seeking to limit, not to
expand, what we can do:
• Facial recognition technologies confirming we are who we say
we are…
• We must resist attempts to universalize this logic:

12. “Good smart" and "bad smart"
• Is the BinCam “good” or “bad”?
• Not forced to recycle
• Appealing to our base instincts:
• Must earn gold bars and rewards!
• Must “compete” with others!
• Must win and impress friends!
• Not treating us as autonomous human beings, capable of
weighing the options by ourselves
• Allowing a recommendation system or Facebook or the
government to do our thinking for us
• What about crowdsourcing systems involving people on
holiday (scuba diving, on cruise, on the beach) in data
collection?

13. Applications

14. Applications
Smartphones, water color and Forel-Ule

15. Smart crowdsourcing
• Do application designers know precisely how we should
behave, so the only problem is finding the right incentive?
• A truly smart crowdsourcing system should make us reflect
on our environmental habits and contribute to conscious
deliberation:
• Letting us benchmark our usual swimming waters against
other waters in our area, instead of trying to shame us with
point deductions and peer pressure
• The task of technology should not be to liberate us from
problem-solving.
• We need to enroll smart technology in helping us with
problem-solving.
• Maybe… in promoting problem solving with a monitoring
twist

16. Smart crowdsourcing

17. Applications, applications
• Improvement of scuba-diving activities
• Ranking the best beaches
• Early-warning systems for HABs and bio-chemical hazards
• Monitoring swell and length of waves
• Water transparency via phone pictures and Secchi disc
• Retrieval of sensor measurements from low-cost moorings

18. From current monitoring to
"participatory environmental science"
• Monitoring and…
• Mobile devices as sensor platforms
• Georeferencing
• Education through citizens’ effective participation
• Community involvement
• Internet-distribution and social platforms to observe and then
share:
• Photos (ocean color, transparency)
• Oil spills
• Algal blooms
• Recommendation
• Decision support
Luigi Ceccaroni - Crowdsourcing and smartphone technology

19. Information acquisition
Luigi Ceccaroni - Crowdsourcing and smartphone technology

20. Information acquisition
Bull. Korean Chem. Soc. 2012, Vol. 33, No. 2
Luigi Ceccaroni - Crowdsourcing and smartphone technology

21. Information acquisition
Sensors 2011, 11, 7055-7062
Luigi Ceccaroni - Crowdsourcing and smartphone technology

22. Information delivery
Luigi Ceccaroni - Crowdsourcing and smartphone technology

23. Information delivery
Luigi Ceccaroni - Crowdsourcing and smartphone technology

24. Information delivery
Luigi Ceccaroni - Crowdsourcing and smartphone technology

25. Information processing
• Standardization, interoperability
• GIS and satellite-data processing, integration and
interpretation
• Data-quality validation in real-time
• Taking into account position, orientation and temperature
• Context-awareness
• Data provided in a more or less voluntary, active or conscious
way
• Metadata and context data: time, location, name, instrument
• Personalisation
• Location
• Social environment
• Profile and personal history
Luigi Ceccaroni - Crowdsourcing and smartphone technology

26. Acquisition, processing,
delivery: a new way
Luigi Ceccaroni - Crowdsourcing and smartphone technology

27. Resources
http://www.citclops.eu/
http://www.coastwatch.org/
http://creekwatch.researchlabs.ibm.com/
http://mwater.co/
http://www.wasserlebnis.de/
http://www.ecy.wa.gov/programs/eap/fw_riv/rv_main.html
http://projectbaseline.org
http://crowd.cs.umass.edu/
http://en.wikipedia.org/wiki/Citizen_science
http://senseable.mit.edu/
http://research.cens.ucla.edu/aquatic/
http://www.secchidipin.org/
http://www.earthobservations.org/geo_me_201211_geo9_ec.shtml
http://www.nurp.noaa.gov/Spotlight/Observatory.htm
http://marine.rutgers.edu/mrs/LEO/LEO15.html
http://root.ew.eea.europa.eu/lltk/papers-citizen-science-and-
lltk/graham_et_al_eos_2011-2-.pdf

28. Crowdsourcing and
smartphone technology
Luigi Ceccaroni, Senior member of research staff
Blue Photonics 2013, Texel (NL), March 18, 2013