trends in embedded computing the ubiquitous computing through sensor swarms
TRANSCRIPT
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Trends in Embedded Computing
The Ubiquitous Computing through Sensor Swarms
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“The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.”
In 1991, Mark Weiser, chief technology officer for Xerox’s Palo
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DefinitionsUbiquitous computing is the method of enhancing
computer use by making many computers available
throughout the physical environment, but making them
effectively invisible to the user
– Mark Weiser
Ubiquitous computing, or calm technology, is a
paradigm shift where technology becomes virtually
invisible in our lives.
-- Marcia Riley (Georgia Institute of Technology, Atlanta.)
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Universal Computing Environment
GamesGames
AudioAudio
DVDDVD
PDAPDA
PCPC
Wash MachineWash Machine LightingLighting
CookerCooker Digital CameraDigital Camera
PrinterPrinter
ScannerScanner
Disk DrivesDisk Drives
NOTEBOOKNOTEBOOK
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Computing Everywhere
• giving machines the ability to detect, track,
and identify people
• to interpret human behavior
• This technology is “fourth generation”
embedded computing: “smart”’
environments and portable or wearable
devices.
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Goals
The key technical goal is
to determine the computer’s context with respect to nearby humans who, what, when, where, and why
so that the computer can act or respond appropriately without detailed instructions.
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The Issues
• the problem of context sensing, which is closely related to the famous frame problem of AI,’ has become a critical problem
• The frame problem is that specifying only which conditions are changed by the actions do not allow, in logic, to conclude that all other conditions are not changed.
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Areas
•person identification
•surveillance/monitoring,
•3D methods
•smart rooms
•perceptual user interfaces
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Users Interface
The multitude of different Ubicomp devices with their different sizes of displays and interaction capabilities represents another challenge
PenGesture recognition…
Mouse
keyboard
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Is it Possible with the present state of art technology
growth??
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• Sensors
• Sensor Networks
• Sensor Swarms
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Berkley Dust
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• Basic board:– Bidirectional, single channel
868 MHz short range radio – Microcontroller – Real-time clock – Calendar circuit
• Sensor board: – 3-axis acceleration sensors– electronic compass– lighting sensor – optic IR-based proximity
detector
VTT Soap Box
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perceptual user interface
• Facial expression
• Hand Gestures
• Whole-body movement
• Voice
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Our Effort in this Direction
• Real Time Signal Processing• Real Time Signal Analysis
– Real Time Matrix Analysis• Eigen Value Problems
– Real Time Optimization
• Emotion/Fatigue/Stress Analysis from Speech• Real Time Video Processing• Real Time Video Analysis• Fatigue/Emotion/Stress Analysis
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Real Time Singular Value Decomposition
• Face Recognition
• Principal Component Analysis
• Speech Processing
• Signal Analysis
• De-noising
• Data Compression
• Page Ranking
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Real Time SVD (key issues)
•Speed
•Accuracy
•Power Consumption
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Our Implementation Trials
• Desktop–Pentium Dual Processor
• TI6713 Floating point DSP
• TI5000 series Fixed Point DSP
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Comparative Assessment of SVD Algorithms on Floating Point Processor
0 20 40 60 80 100 120 140 160 180 2000
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04comparsion of Time complexities
order of autocorrelation matrix
cpu
pro
cess
ing
tim
e in
(se
cs)
QR FactorizationGolub-kahan algorithmfast singular value algorithm
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0 20 40 60 80 100 120 140 160 180 2000
0.005
0.01
0.015
0.02
0.025comparsion of Time complexities
order of autocorrelation matrix
cpu
pro
cess
ing
tim
e in
(se
cs)
QR factorization
Golub-kahan algorithmFast singular value algorithm
Comparative Assessment of SVD Algorithms on Fixed Point Processor
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Comparative Accuracy
0 50 100 150 200 250 3005
6
7
8
9
10
11
12
13
14
15comparsion of accuracy plots
order of autocrrelation matrix
per
cen
tag
e er
ror
QR factorization
Golub-Kahan algorithmFast singular value algorithm
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Designing Power Efficient Algorithms
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Why Power Efficiency in Low Power
• Stand Alone Systems• Battery Driven• Battery capacity is limited• It is possible to decrease the Battery discharge
rate by Intelligent use of its power – DVS: stands for Dynamic Voltage Switching– Hardware: reconfiguration and intelligent clock
throttling– Software: Code Size Minimization and Run Time
optimization
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Typical State Transitions for Power Saving
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Power Management in Pentium M
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Intel 90 nm – Pentium M Processor (2 MB cache)
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Power Density in Pentium M byInfra-Red Emission Microscopy