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[bone shaker] :: DIY health final

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  • Measurement, psychology, urban/city
  • “ layer of the poetic” to the system (make it human) How can this data be most effectively represented?
  • “ layer of the poetic” to the system (make it human) How can this data be most effectively represented?
  • “ layer of the poetic” to the system (make it human) How can this data be most effectively represented?
  • “ layer of the poetic” to the system (make it human) How can this data be most effectively represented?
  • “ layer of the poetic” to the system (make it human) How can this data be most effectively represented?
  • “ layer of the poetic” to the system (make it human) How can this data be most effectively represented?
  • “ layer of the poetic” to the system (make it human) How can this data be most effectively represented?
  • “ layer of the poetic” to the system (make it human) How can this data be most effectively represented?
  • MAKE THIS SIMPLER. Space and emotion… Affect of the city on the psyche… Serendipity 
  • MAKE THIS SIMPLER. Space and emotion… Affect of the city on the psyche… Serendipity 
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    • 1. Kimi Spencer [email_address] Bone Shaker DIY Health, Final Proposal | 14 November 2011
    • 2. “ A state of complete physical , mental , and social well-being and not merely the absence of disease or infirmity .” World Health Organization
    • 3. Health for Me Excitement, delight, and adventure. Absence of boredom; stimulation. Discovering meaningful connections. Joie de vivre .
    • 4. The Situationist Lived experience over the spectacle . Derive (“t0 drift”) the spontaneous exploration of urban landscapes guided by aesthetic instinct .
    • 5. Biking and the City Biking is an urban phenomena. Specific to cities with a vibrant cityscape and infrastructural support . A tool for expanded exploration .
    • 6. Biking and Health “ A Copenhagen study of over 30,000 people ranging in age from 20 to 93 took place over 14.5 years and found that bike commuting an average of 3 hours per week decreased risk of mortality by about 40% over the control group that did not bike” Andersen, 2000
    • 7. Smallest Target Behavior Bike for 30 minutes per day .
    • 8. The User Urban city dweller. 20 to 30 years old. Educated , and technologically comfortable . Moderately well-off ( can afford a bike and smart phone ). Not an athlete .
    • 9. The User’s Ability Safety issues. Bike paths. Places to lock bikes. Time . Routine . Effort .
    • 10. Spokes NYC
    • 11. Ride the City
    • 12. The User’s Motivations Social acceptance /rejection. Biking is cool. Pain /Pleasure. Easily bored by repetition and lazy. Hope /Fear. Desire to get physically fit.
    • 13. The User’s Motivations How to bring pleasure? It’s not about exercise, it’s about exploration . How to catalyze hope? Feedback on user’s progression .
    • 14. Bikes as a Catalyst for Adventure
    • 15. Classify the Behavior
    • 16. The Environment Urban landscape, Sound data Temperature data Networks data … Layers of information
    • 17. Hertzian Space The invisible frequencies that are “pervasive, and though invisible, in some way are present in every aspect of our physical experience”. Both real and imaginary . “ The dreams of electronic objects.”
    • 18. Immaterials
    • 19. Wiggle
    • 20. WarBiking
    • 21. Second Order Goal Experience the layers of the City though exploration .
    • 22. Proposal An application that promotes urban biking by enabling users, and the exploration of the urban landscape in a new, delightful way.
    • 23. Cybernetic Model
    • 24. Network Diagram
    • 25. Triggers Reminders after inactivity. Suggestions of places, events, layers, and times to bike. Notifications on friends’ urban adventures and biking activity.
    • 26. Mobile, Real-Time Feedback Personal health data. City data.
    • 27. Cyclemeter
    • 28. Copenhagen Wheel
    • 29. Aesthetic Artifacts Positive reinforcement . Sharing and social perception.
    • 30. Nike+ Storefront
    • 31. Mobile Logger
    • 32. Thank you.