EndUser Programming of Assistive Monitoring Systems Alex Edgcomb Frank Vahid University of California Riverside Department of Computer Science 1 of 16 Motion sensor Sensors and actuators in MNFL 1 for enduser programming ID: 465710
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Feature Extractors for Integration of Cameras and Sensors during End-User Programming of Assistive Monitoring Systems
Alex EdgcombFrank VahidUniversity of California, RiversideDepartment of Computer Science
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Motion sensorSlide2
Sensors and actuators in MNFL [1] for end-user programming
Alex Edgcomb, UC Riverside2 of
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“Person at door”
LED lights in house
“Person at door”
Outdoor motion sensor
Doorbell
Assistive monitoring
User customizability essential [2][3]
[1] Edgcomb, A. and F. Vahid. MNFL: The Monitoring and Notification Flow Language for Assistive Monitoring. Proceedings
2nd ACM International Health Informatics Symposium, 2012. Miami, Florida.
[2] Philips, B. and H. Zhao. Predictors of Assistive Technology Abandonment. Assistive Technology, Vol. 5.1, 1993, pp. 36-45.
[3] Riemer-Reiss, M. Assistive Technology Discontinuance. Technology and Persons with Disabilities Conference, 2000.Slide3
Porch light
LED lights in house
Expanding the previous example
Alex Edgcomb, UC Riverside
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“Person at door”
“Person at door”
Outdoor motion sensor
Doorbell
Light sensorSlide4
Webcams are cheap
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Webcams can do more than sensors
Fall down at home
In room for extended time
Can do same as some sensors
Motion sensor
Light sensor
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Alex Edgcomb, UC Riverside
Identify person
at front doorSlide6
Problem: Integration of webcams and sensors
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Homesite
Commercial approach:
Alex Edgcomb, UC Riverside
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Outdoor motion sensorSlide7
Solution: Feature extractor
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92
Integer stream output
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100
Alex Edgcomb, UC Riverside
Extract some feature
Video stream inputSlide8
Identify person at door in MNFLAlex Edgcomb, UC Riverside
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Outdoor motion sensorSlide9
Person in room for extended period of time in MNFL
9 of 16Video’s YouTube linkAlex Edgcomb, UC RiversideSlide10
Many feature extractors are possible
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Are feature extractors usable by lay people? Two usability trials.
51 participantsTrials required as 1st lab assignmentNon-engineering/non-science students at UCR
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Participant reference materials
One-minute video showing how to spawn and connect blocks.Overview picture
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Example challenge problem
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actual participant solutionSlide14
Trial 1: Increasingly challenging feature extractor problems
25 participants14 of 16
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Trial 2: Feature extractor vs logic block
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ConclusionsFeature extractors
Elegant integration of cameras and sensorsQuickly learnable by lay peopleFuture workDevelop additional feature extractor blocksTrade-off analysis between privacy, communication, and computation16 o f 16
Alex Edgcomb, UC Riverside