Ubiquitous Computing Lecture 2

1. Ubiquitous ComputingLecture 2 Hoon OhUniversity of Ulsan

2. Introduction to Ubiquitous Computing

3. Ubiquitous (Pervasive) Computing • Bring computing into our everyday activities in the physical world • What is the most natural way to access & interact with the bits in the digital world? • PCs with keyboard & mouse, monitors? • Mobile phones with tiny keypad & tiny screen? • Digital TVs? • Game consoles? • Digital Watches? • Combination of all of them?

4. Natural Interaction with the Bits (Digital World) • Maybe not be through any of these unfamiliar digital access devices! • What if familiar physical objects can also become our interface to the digital world? • Desk, wall, floor, chair, refrigerator, papers, bed, • As if computing devices have disappeared … • Interaction with the digital world is through interaction in the physical world.

5.  Ubicomp Applied to Healthcare • What is the natural way of delivering online/Internet care to elders at home? • PC-like devices (Notebook PCs, PDAs, cell phones, etc.)? • Elders’ ADLs do not naturally involve PC-like devices • But naturally involve everyday objects in their physical surrounding • Example: good-dietary service • Create an information website? • Built into a dining table * ADL: Activities of Daily Living

6. ADLs (예) • 의식 및 사람 알아보기 • 대소변 가리기 • 침실에서의 움직임 • 식사 • 이동 • 옷갈아 입기 • 개인위생 (치솔질, 세면 등) • 목욕 • 화장실 이용 • 계단오르기 • 식사준비 • 세탁 • 금전관리 • 전화기 사용 • 외출 • 대중교통 이용

7. Invisible and Disappearing Computer (Weiser) • Why invisible and disappearing”? • Technology makes lives easier or more difficult (for ordinary people)? • “Usability “ and “simplicity” • Better with nothing-never-nowhere computing

8. Invisible and Disappearing Computer (Weiser) • Unless necessary, don’t make people operate complex machines to get digital services. • Project Aura (CMU) “The most precious resource in a computer system is .. User Attention. Today's systems distract a user in many explicit and implicit ways, thereby reducing his/her effectiveness.”

9. Smart Everyday Objects • How to make computing invisible and disappearing? • Hide computing into everyday objects • Embed computing into familiar everyday objects • computing, sensing, and networking capabilities • Everyday objects understand you & environment (context-aware computing). • Context = 5Ws (who – when – where – what – how)

10. Smart Everyday Objects (Examples) • Bionic Running Shoes (Adidas) • Posture Chair (MIT media lab) • Moving Portrait (MIT media lab)

11.  More Examples of Smart Objects • History table cloth (EU Equator) • Emotional Décor (NYU) • I/O Brush (MIT)

12. More examples • Chameleon Mug • LCDs, bimetal strips, thermoresisters and thermochromic ink as sensors • A vessel which changes color, displays safety messages and/or springs a handle to demonstrate whether the fluid in it is hot or cold. • various sensors could detect the concentration of sugar or lactose in a beverage, warn of bad milk or mix the fluids ultrasonically. • MediaCup

13.  Surface Computing (Microsoft Research) • A new way that is so familiar to us. • A new way that isn’t really new.

14.  Maybe not so smart objects • Casio Color Wrist Camera • Dada MP3 player shoes • LG Internet fridge • Credit Card Barbie Doll (from Accenture)

15.  Would you buy it for twice the price? Please Vote

16.  LED Display Cloth

17. A Wearable Display for Team Sports(U. of Sydney)

18. A Wearable Display for Team Sports (U. of Sydney)

19.  Topobo (MIT)

20.  Blendie (MIT) • A “sensitive” blender that can express emotion.

21.  Case Studies • Diet-aware Dining Table (PERVASIVE 2006) • Geta Sandals (Personal & Ubiquitous Computing) • Object Locator Ring & Watch

22. Case Study 1: Diet-aware Dining Table Detect what and how much you eat from the table • Sensing to recognize behavior • Combine weight sensor and RFID sensors to track food transfer among containers • Interaction • Natural user eating behaviors become system input (no need to operate any devices). • How do you design a user interface without affecting one’s appetite?

23. Diet-Aware Dining Table: Single Interaction Example • Bob pours tea from the tea pot to personal cup, and drinks it • Put on tea pot. • RFID tag appears • Weight increases ∆w3 • Pour tea! • |∆w3 - ∆w1 | ≈ ∆w2 • Pour tea? • Weight increases ∆w2. • Pick up tea pot. • RFID tag disappears • Weight decreases ∆w1

24. d2 d1 Case Study 2: Geta SandalsShoes (Slippers) that track where you walk • Track people’s locations with minimal infrastructure in the deployed environment • Footstep-based localization • Error accumulation (1~10%) • Location-aware RFID tags

25. Continues • Theoretical lower limit is given by Nyquist sampling theorem: • Any time-continues signal of bandwidth B can be reproduced faithfully from its sampled values, if and only if the sampling rate is 2B or higher • Example CD • Bandwidth: 22050 Hz (given by human ear) • Sampling Frequency: 44100 Hz

26. Case Study 3: Object Locator Ring (Watch)Track locations of everyday things • Where did I put these everyday things? • Glasses, cell phones, wallets, keys, remote controls, … • Track locations of everyday things • RFID reader on ring • RFID tags on everyday objects • Ultrasonic Indoor location systems (MIT Cricket)

27. How does it work? • Assumption: • Most objects are moved by hands • Picking up phone: • Phone presence (RFID tag) detected by the ring antenna • Carrying the phone: • Continuous presence (on-hand) • Non-presence (pocket-it) • Dropping the phone: • Phone presence (RFID tag) not detected by ring antenna • Location of the object?

28. Part II: Persuasive Objects (Smart environment, smarter people)

29.  Persuasive Computing • Consider a frequent “ where are my (misplaced) things?” person … • Possible solutions • Build an object location tracker • Build a beeper that remind misplaced objects • Which one is more effective use of technology?

30.  Can digital technology be used to help us … • Eat healthy • Exercise more • Drive safely • Quit smoking • Become more tidy • Control spending • Dress style

31. Persuasive computing (objects) • Baby Think It Over • Textrix VR Bike • Slot Machine • Smart Tachograph (ETH)

32. Case Studies • Playful tray (UbiComp 2007) • Playful toothbrush (CHI 2008) • Mug-Tree (UbiComp 2007) • Nutritional-aware kitchen (CHI 2007, PERSUASIVE 2008) • Clean-your-room poster • ChroMirror (CHI 2008) • Mug-Forest (New)

33. Case Study 1: Playful TrayEncourage good eating habit in young children • Sense to recognize behavior • Weight sensor underneath the tray to sense eating actions • Eating actions as game input • Play to engage behavior change • Interactive games: coloring cartoon character or penguin fishing • User study on 4 children (autistic)

34. Case Study 2: Playful Toothbrush Encourage proper and thorough brushing for young children • Bad teeth for young children with cognitive impairments) • Sense to recognize behavior • Webcam to detect brushing motions • Brushing actions are game input • Play to engage behavior change • Start with a mirror image of dirty teeth. • Physical brushing maps to virtual plaque removal • User study on 13 kindergarten children Web camera for tracking brushing motions Camera #2 to record videos for later human analysis Brushextension Brushing game

35. Case Study 3: Mug-Tree Encourage healthy habit of drinking fluid regularly • Sense to recognize behavior • Tilt sensor to detect drinking actions • Drinking actions are game inputs • Play to engage behavior change • Game metaphor: hydrating/dehydrating body -> watering/drying a tree

36. Case Study 4: Nutrition-aware KitchenRaise awareness of nutritional fact to everyday family cooks • Sense to recognize behavior • Combine weight and camera sensors to detect cooking actions (change food ingredients) • Voice input for food ingredient label • Food ingredients -> meal calories • Play to engage behavior change • Overcooking calories -> overweight on a family member • Imbalance the seesaw board -> big boulder sliding down

37. Case Study 4: Nutrition-aware Kitchen Raise awareness of nutritional fact to everyday family cooks • Awareness • User study on 3 family cooks name of ingredients, total calorie in this container, and the most recent calorie change (b) (a) recommended calorie needs current calorie in use in total (c) calorie of finished course Figure 7. User interface of Calorie-aware Kitchen, including (a) overview of calorie in the system; (b) recommended calorie needs and current used calories; (c) a calorie-aware game with a beloved family member to bring enjoyment of calorie control

38. Case Study 5: Clean-your-room poster Persuade young children to put things back where they belong after using them • Sense to recognize behavior • RFID sensors to check if things were put back in the shelf • Play to engage behavior change • Misplaced things -> trash in the virtual world • Using child's sympathy for the animal to persuade the child to put things back to where they belong.

39. Case Study 6: ChroMirrorPersuade people to explore more colorful dressing • Sense to recognize dress & dressing color • Camera and Computer Vision • Play to engage behavior change • Easily and playfully explore & experiment with how different clothing color look on people

40. Case Study 7: Mug-Forest • Can a mobile phone do more than a notebook PC? • Mobility (always with a user), small form factor, • Can a mobile phone be extended for non-verbal communication?

41. Case Study 7: Mug-ForestUse social pressure for persuasion • Sense to recognize drinking action • Accelerometer (in a phone) to detect drinking action • Camera to detect water level • Play to use “social pressure” to engage behavior change • Computer-mediated human persuasion, not computer persuasion

42. Questions & Answers Check out our projects & papers NTU Ubicomp Lab http://mll.csie.ntu.edu.tw