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Sensor-Based Interactions

Sensor-Based Interactions. Kami Vaniea. Outline. Coping with Uncertainty Making Sense of Sensing Systems: Five Questions for Designers and Researchers Distributed Mediation of Ambiguous Context in Aware Environments. Uncertainty.

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Sensor-Based Interactions

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  1. Sensor-Based Interactions Kami Vaniea

  2. Outline • Coping with Uncertainty • Making Sense of Sensing Systems: Five Questions for Designers and Researchers • Distributed Mediation of Ambiguous Context in Aware Environments

  3. Uncertainty State of knowledge in which one or more alternatives result in a set of possible specific outcomes, but where the probabilities of the outcomes are neither known nor meaningful.

  4. Uncertain Communication • Sensors produce concrete data with uncertain or ambiguous interpretation • Location Data (GPS) • Temperature • Computers can make bad decisions based on uncertain data • Interrupting user • Making poor decisions on user’s behalf • Communicating wrong information

  5. Outline • Coping with Uncertainty • Making Sense of Sensing Systems: Five Questions for Designers and Researchers • Distributed Mediation of Ambiguous Context in Aware Environments

  6. HHI and HCI • Human to Human Interaction (HHI) has been well studied by researchers • How can we use some of the lessons about Human to Human communication to facilitate Human to Computer communication? • Recognize that communication is a shared responsibility and requires management and repair

  7. Norman’s Seven Stages of Action • Forming the goal • Forming the intention • Specifying an action • Executing the action • Perceiving the state of the world • Interpreting the state of the world • Evaluating the outcome Goal Execution Evaluation

  8. Five Issues in Communication • Address: Directing communication to a system • Attention: Establishing that the system is attending • Action: Defining what is to be done with the system • Alignment: Monitoring system response • Accident: Avoiding or recovering from errors or misunderstandings

  9. Stages of Action vs. Conversation Issues Address Human System Attention Action Alignment Accident

  10. Address: How do I address or of many possible devices? • GUI Answers • Keyboard • Mouse • Exposed Challenges • Disambiguate signal-to-noise • Disambiguate intended target system • How to not address the system • Possible Problems • No response • Unwanted response

  11. Attention: How do I know the system is ready and attending to my actions? • GUI Answers • Graphical feedback such as blinking cursors • Exposed Challenges • Giving feedback so the user knows it has the system’s attention • Periphery feedback • Possible Problems • Wasted input if system not responding • Unintended action • Privacy and Security problems(?)

  12. Action: How do I effect a meaningful action, control its extent and possibly specify a target or targets of my action? • GUI Answers • Use standard GUI widgets, such as clicking and selecting text, to interact with the system • Exposed Challenges • Identifying and selecting possible actions • Avoid unwanted selection • Handling complex operations • Possible Problems • Limited operations available • Failure to execute action • Unintended action

  13. Alignment:How do I know the system is doing the right thing? • GUI Answers • Graphical feedback such as text appearing • Auditory feedback • Detectible new state • Exposed Challenges • Making system state perceivable • Providing distinctive feedback on results and state • Possible Problems • Differentiation problems • Inability to detect mistakes • Unrecoverable problems

  14. Accident: How do I avoid mistakes? • GUI Answers • Control/guide in direct manipulation • Stop, cancel, undo or delete • Exposed Challenges • Controlling or canceling system actions in progress • Disambiguating what to undo in time • Intervening when user makes obvious error • Possible Problems • Unintended action • Inability to recover state

  15. Discussion • UbiComp is still a new growing field • Now is the time to create new methods of interaction between Humans and Machines

  16. Outline • Coping with Uncertainty • Making Sense of Sensing Systems: Five Questions for Designers and Researchers • Distributed Mediation of Ambiguous Context in Aware Environments

  17. Ambiguous Context Data • Many systems are based on the assumption that context data is unambiguous • However, accurately determining context is a hard problem since the system isn’t in possession of all the facts • Techniques such as AI algorithms can be applied but are not always accurate and require some training • Sometimes it is necessary to ask the human in order to get unambiguous context data

  18. Architecture of the Extended Context Toolkit

  19. Disambiguating Sensor Data • In an ubiquitous system where all the devices behave in a distributed manor disambiguating data is a shared problem

  20. Issues in Building Realistic Context-Aware Applications • Distribution: Devices are in a distributed environment • Storage: When should ambiguous data be stored? • Multiple Subscription Types: Allow subscribers to opt-in/out and choose their type of subscription • Pre-emption of Mediation: Prevent multiple simultaneous mediations • Forced Mediation: Request mediation by other devices • Feedback: Provide feedback to users about what the system thinks is happening

  21. Storage • Should ambiguous data be stored? • Should mediated data be stored? • Both? • How do we store ambiguous data since it is actually a graph of options • Storing only unambiguous data is easier

  22. Subscribers • Opt-in and Opt-out subscriptions allow subscribers to get only what they want and no more • Those who get ambiguous data will have to mediate it, wait for another to mediate it or force mediation

  23. Pre-Emption of Mediation • Mediation may occur simultaneously in several components • If several components are mediating at once the first one to succeed pre-empts the others • Does this mean the users will get multiple requests for mediation?

  24. Forced Mediation • If a subscriber is unable or doesn’t want to mediate it can request another component to mediate • It passes all ambiguous data to the other component which mediates if possible

  25. Feedback • Provide feedback about what the system is doing and what its current state is • Feedback can come in many forms from messages to speech

  26. Examples • In/Out Board • Monitored when residents of a single building where present or not • CybreMinder • A situation aware reminder system which can use situational data to trigger reminders • Word Predictor • Makes typing words easier since it guesses context

  27. Questions?

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