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Crowdsourcing data for consumer-ready environmental monitoring
- 1. HUMANLOGIC.COM Crowdsourcing data for consumer-ready environmental monitoring Prepared for Tufts University Department of Computer Science Host: Professor Ming Chow Karen Donoghue and Craig Newell HumanLogic
- 2. HUMANLOGIC.COM Thank you for joining! We’re recording and we will take Q&A at the end via chat
- 3. HUMANLOGIC.COM Interaction design for IoT devices at large scale
- 4. HUMANLOGIC.COM What is Particulate Matter (PM)? (also called also called particle pollution)
- 5. HUMANLOGIC.COM Source: © Encyclopédie de l’Environnement PM10 <= 10 𝞵m PM2.5 <= 2.5 𝞵m PM1 <= 1.0 𝞵m Coarse particles Upper respiratory tract Fine particles Lower respiratory tract Very fine particles Alveolus (tiny air sacs)
- 6. HUMANLOGIC.COM The rise of low cost PM sensors
- 8. HUMANLOGIC.COM Basic Data Gathering IoT System
- 9. HUMANLOGIC.COM ● Laser PM Sensor ● Microcontroller ● Case
- 11. HUMANLOGIC.COM ● WiFi as almost everyone has it without extra costs ● HTTPS for simplicity over MQTT, etc.
- 13. HUMANLOGIC.COM
- 15. HUMANLOGIC.COM ● HTTPS ● Efficiency ● Cacheability ● Validity
- 16. HUMANLOGIC.COM
- 17. HUMANLOGIC.COM Local Haze crowdsources air quality sensor readings worldwide and rates sensor accuracy
- 18. HUMANLOGIC.COM
- 19. HUMANLOGIC.COM See Local Haze demo video on YouTube: https://youtu.be/Ex85q6zH8rc
- 20. HUMANLOGIC.COM Lessons learned for building IoT systems
- 21. HUMANLOGIC.COM What user experiences work best for dealing with lots of things?
- 22. HUMANLOGIC.COM “At scale”: many, thousands, hundreds of thousands, millions, tens of millions...
- 23. HUMANLOGIC.COM Ease of use as a core attribute
- 24. HUMANLOGIC.COM
- 25. HUMANLOGIC.COM To help manage the size of the infinite scrolling list we added filtering
- 26. HUMANLOGIC.COM
- 27. HUMANLOGIC.COM After filtering, we added relevancy
- 28. HUMANLOGIC.COM
- 29. HUMANLOGIC.COM We added a map view to help users better understand the contents of the list
- 30. HUMANLOGIC.COM
- 31. HUMANLOGIC.COM Understand what attributes of the data impact perception of “trustworthiness”
- 33. HUMANLOGIC.COM Use the best interaction model(s) based on users’ needs - may need multiple
- 34. HUMANLOGIC.COM
- 35. HUMANLOGIC.COM Thank you! Send your questions via chat
Editor's Notes
- Karen: Introduction
- CHECK COPYRIGHT OF IMAGE PM PM10 : inhalable particles, with diameters that are generally 10 micrometers and smaller; and PM2.5 : fine inhalable particles, with diameters that are generally 2.5 micrometers and smaller (The average human hair is about 70 micrometers in diameter – making it 30 times larger than the largest fine particle.
- HTTPS Polling vs Push Efficiency Just the needed data Cacheability No need to download it if nothing has changed Validity How long is the data valid for? When should the next poll happen?
- Targeting consumers that are also technical citizen scientists
- Over 18K sensors
- Note that with the correct technical implementation using techniques such as lazy loading, speculative loading, etc….
- May not know how often the data is being refreshed
- What is the future of interaction design for large numbers of entities? - search and rule based interactions To what extent is query language design important in designing for these kinds of interaction models? What skills are needed for designers of these “at scale” systems? What roles do these practitioners play in organizations?