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Nurturing Natural Sensors

Nurturing Natural Sensors . UbiComp 2011 Best Paper Stacey Kuznetsov , William Odom, James Pierce, Eric Paulos Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh, PA, USA 呂孟林. Outline. Introduction Methods Discussion Conclusion. Introduction. Majority

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Nurturing Natural Sensors

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  1. Nurturing Natural Sensors UbiComp 2011 Best Paper Stacey Kuznetsov, William Odom, James Pierce, Eric Paulos Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh, PA, USA 呂孟林

  2. Outline • Introduction • Methods • Discussion • Conclusion

  3. Introduction • Majority • Electronic instantiations of sensing devices • Visionary • Non-digital sensing to reflect environments • Everyday biomarkers: common biological organisms that express information about an ecosystem or its many parts • Expand UbiComp visions of sensing to include living organisms themselves

  4. Introduction • Opportunity for future ubiquitous sensing • Non-digital sensors • Designing technologies that teach new ways of ‘seeing’ • Enriching practices of data collection and sharing

  5. What can be a sensor? • Reptile posture suggesting a disturbance to the environment • Scale larvae (幼蟲) signifying a pest problem • Bee behavior reflecting local weather and bloom cycles • Fish appearance indicating water quality and parasite levels

  6. Where are the sensors? • Activity recognition and infrastructure sensing • Wearable sensors, mobile phones sensors or sensing surrounding infrastructure • Active participatory sensing • Handheld air quality monitors • Passive environmental monitoring • Autonomous robots or sensors in daily life

  7. Input techniques • Detecting human actions • Direct manipulation: touch and gesture sensing technologies • Natural User Interfaces (NUI) • Contrast to GUI • Without learning • Make the user feel like a natural

  8. Methods • Semi-structured interviews with 10 participants • Walk through their daily routines to know their tools and local settings • Audio recorded all interviews and took field notes

  9. Participants • Members: • Organic farming, urban agriculture group [F1, F2, F3] • Organic gardening, independent [G] • IPM (integrated/organic pest management), city zoo [I] • Beekeeping, urban beekeeping community [B1, B2] • Horticulture, independent [H] • Aquarium and fish keeping, city zoo [A] • Reptile keeping, city zoo [R] • Participants’ backgrounds are all professional. • Motivation: income, enjoyment and contribution

  10. Findings • Monitoring practices • Use of technology or traditional tools and observation-based • Types of living indicators • Use living organisms as environmental indicators • Collection, sharing and speculation • How to process biomarker data

  11. Monitoring practices

  12. Monitoring practices • Regular check-ups • Daily, weekly, or routinely rounds • Starting with technology • Ending with traditional instruments or observation

  13. Technology-mediated monitoring • Routine digital sensing • Thermometer: saving animal from losing temperature • Weather report: when raining, flower can’t secrete nectar; when too cold, too day, it’s the same. • ORP sensor: to ensure proper function of the ozone generator • Scale: to make sure the animal is healthy • Soil tests

  14. Technology-mediated monitoring • Occasional digital sensing • Plants grow not properly: pH problem or a nutrient deficiency • Unusual fish behavior: pH, light or oxygen • The amount of fermented honey: refractometer with 18% threshold • Abandoned digital sensing • No sprinkler due to faulty humidity sensing • No testing soil but observing plant growth

  15. Traditional or observation-based • Magnification and counting tools • Beekeeping: monitoring tray with square inch grid • Handmade traps: to catch insects • Magnifying hand lens: to observe the stages of beneficial larvae on leaves • High-resolution microscope: to check various parasites of fish

  16. Traditional or observation-based • Monitoring through physical engagement and action • taps plants to let clouds of whitefly to emerge • tip beehive to gauge its weight and infer the amount of nectar • Stick finger into soil to measure the moist of soil • Scuba dive into tank to monitor fish appearance and behavior

  17. Traditional or observation-based • Monitoring through ‘naked’ observation • Smell: to check if the ammonia is in the water • Sight: to see what’s germinating can tell the temperature • Taste: to identify the flower the bees get • Hearing: to know the planting time by hearing the bird mating calls • Touch: to detect pest by feeling sticky on the leaves

  18. Types of living indicators

  19. Types of everyday biomarkers • One-to-one • For the bees, chicken coop smell = deadly bacterial infestation; piping sound = new queen is ready • Green water = ozone deficiency • Saw dust at the bottom of vine plants = borer pest • Hydrangea color = soil pH value • Accentuated leaf growth = too much nitrogen • One-to-many • A yellowing “between veinof leaves”=nutrient deficiency or pH imbalance • Blossom end rot in tomatoes=lack of calciumor moisture content • Sliming fish = poor water quality or a parasite • Trembling bees = sprayed or got contaminated by chemical

  20. Types of everyday biomarkers • Ecosystem • Local drought and blooming cycles by observing the bees • Tracking the balance between pest and beneficial insects for monitoring the greenhouse • Coral reef bleaching as a response to stress or disturbance to the system • The endangerment of the Philippine crocodile suggesting “pollution, habitat loss • Diseases prevailing on unhealthy plants

  21. Collection, sharing and speculation

  22. Data collection, sharing and speculation • Data collection • Daily logs of water quality and feedings • Extensive log and computer database of pest infestations • Recipes of honey products • Schedules and layouts for crop rotations • Gardening journal • Sharing Mechanisms • Sharing Mechanisms • Casual conversation, e-mail, facebook, twitter, books, blogs, radios and speaking to zoo visitors

  23. Data collection, sharing and speculation • Speculation based on data and sharing mechanism • Through discussion and blog to know weather pattern allows stink bugs to reproduce rapidly • Urban water quality affects the growth of the plants and the fish due to chlorine, fluoride and other chemicals use for disinfection • Colony Collapse Disorder (CCD)in honeybees due to the pesticides or genetically modified plants • Nitrogen soil deficiencies due to chemical sprays on the yards • The endangered Louisiana Pine Snake due to the disappearing habitat of their food source pocket gopher causing by forest management

  24. Discussion • Highlight participants’ proficiency with technologies and rely on biomarkers to infer information about the environment • Biomarker systems • The interdependency between using biomarker and technological sensors • Active engagement with context • Direct interact with the environment • Involved in the social and political processes

  25. DESIGN IMPLICATIONS AND OPPORTUNITIES • Leveraging non-digital inputs • Designing technologies that teach new ways of seeing • Enriching practices of data collection and sharing

  26. Leveraging non-digital inputs • Expanding the UbiComp community’svision of sensing beyond electronic devices, to includeliving organisms and traditional tools • Shift from designing sensing technologies to designingubiquitous systems that incorporate living organisms and traditional tools along with digital devices, either active or passive

  27. New ways of seeing • Skilled technologies abandoned after participants developed a skill • Support new ways of seeing or engaging with the environment • Encourage human awareness, refection and wonderment about our living world • Embracing low-fidelitysignals • Imprecise sensing practices of biomarkers and traditional tools • With indiscreet input and to embrace ambiguity

  28. New ways of seeing • Peripheralengagement • To know the whole system by observing peripheral biomarkers • Scaffolding (鷹架) • New scaffolding tools that train individuals and groups to ‘sense’ better and differently • Activity recognition and participatory sensing appropriates mobile phones as digital sensing devices • sensing as a conjoint practice, tool for community togetherness

  29. Data collection and sharing • Recorded in logs, databasesand personal journals through causal conversation, blogs, radio and so on. • Opportunities for existing and future citizen science applications to incorporate individuals working with living systems • Community concern and political interest • Collective action around shared issues • Using the scaffolding tools for biomarker data of everyday life

  30. Conclusion • Fluent but without a clear structure, due to no section or paragraph number. • In overall, it’s a good article with nice sentence rather than a good paper.

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