Intelligent Sensors
     2010 - 2020!

             I <3
           sensors




 Jonas Lamis - SciVestor
1,000,000

1,000,000,000,000

18,446,744,073,709,551,
615
The Law of Accelerating Returns




                     Courtesy Ray Kurzweil and Kurzweil Technologies
B4 + C
http://www.flickr.com/photos/maxkiesler/2240153169/
Why Create a Driverless Car?
ISGR
SENSING

THOUGHT
Brain sensors
Ray and Terry
http://www.flickr.com/photos/doctorow/2403369880/
http://www.flickr.com/photos/wipeout/179788993/
23 and Me
http://www.flickr.com/photos/takomabibelot/417896166/
http://www.flickr.com/photos/hackshaven/2228724569/
SMART




DUST
SMART




DUST
Business
                                                     Logic

                                                     ...
Answers
the
ques,on:

Answers
the

ques,on:
                                                    Where
am
I?



           ...
Higher‐Level
Domain

                                             Knowledge
and
Applica,on‐
                              ...
2004 DGC Landscape of
                       Technologies
                                                                ...
2005 DGC Landscape of
                             Technologies
                                                          ...
2007 DUC Landscape of
                             Technologies
                                                          ...
Market beats
                  Global Meltdown
                                                  expectations


          ...
Listen up humans.
 SciVestor provides research and consulting on
emerging technologies that will change the world.


     ...
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
Intelligent Sensors: 2010 - 2020
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Intelligent Sensors: 2010 - 2020

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Jonas Lamis from SciVestor presented this presentation at RobDevelopment, November 2008.

Published in: Technology
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  • Hi!
    nice article about sensors!
    You might also find interesting our latest article: 'Sensors for mobile phones: more data, more services, more profit!' - http://droidsensors.com/2010/02/sensors-for-mobile-phones-more-data-more-services-more-profit/
       Reply 
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  • Looks great. Where can one find the speaker notes or audio to go with it?
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Intelligent Sensors: 2010 - 2020

  1. 1. Intelligent Sensors 2010 - 2020! I <3 sensors Jonas Lamis - SciVestor
  2. 2. 1,000,000 1,000,000,000,000 18,446,744,073,709,551, 615
  3. 3. The Law of Accelerating Returns Courtesy Ray Kurzweil and Kurzweil Technologies
  4. 4. B4 + C
  5. 5. http://www.flickr.com/photos/maxkiesler/2240153169/
  6. 6. Why Create a Driverless Car?
  7. 7. ISGR
  8. 8. SENSING THOUGHT
  9. 9. Brain sensors
  10. 10. Ray and Terry
  11. 11. http://www.flickr.com/photos/doctorow/2403369880/
  12. 12. http://www.flickr.com/photos/wipeout/179788993/
  13. 13. 23 and Me
  14. 14. http://www.flickr.com/photos/takomabibelot/417896166/
  15. 15. http://www.flickr.com/photos/hackshaven/2228724569/
  16. 16. SMART DUST
  17. 17. SMART DUST
  18. 18. Business Logic Basic Awareness Sensory Enablement http://www.flickr.com/photos/liberato/171610084/
  19. 19. Answers
the
ques,on:
 Answers
the
 ques,on:
 Where
am
I?
 e What’s
around
 Mobi rformanc nsing me?
 le Se Basic Awareness Pe High Goal Logic Execution Answers
the
ques,ons:
 Makes
the
statements:
 Am
I
behaving
correctly?
 Do
this
and
that.
 Am
I
doing
anything
 dangerous?

  20. 20. Higher‐Level
Domain
 Knowledge
and
Applica,on‐ specific
opera,ons
 implemented
here
 e Mobi rformanc Complex
business
rules
 nsing Interac>ng
with
society
 le Se Basic Awareness Pe High Goal Logic Execution 100%
of
an
applica,on
developer’s
,me
 should
be
spent
here

  21. 21. 2004 DGC Landscape of Technologies 5
–
10%
of
team
capacity
was
spent
 30
‐
60%
of
team
capacity
 on
collec,ng
GPS
data.

 was
spent
enabling
mobile
 sensing
technologies.
 Mature
and
well‐established
high
 performance
GPS
market
enabled
 e Mobi rformanc nsing developers
to
focus
on
higher‐level
 Prevalent
Technologies:
 func,on
of
GPS
waypoint
traversal.

 le Se  SICK
 Prevalent
Technologies:
 Basic Awareness Pe  BOSCH
  NAVCOM
 High  Custom
Vision
Solu,ons
 Goal  Arrow
 Logic  Trimble
 10
–
30%
of
team
capacity
spent
 wri,ng
the
same
“commodity”
 Execution naviga,onal
algorithms
as
other
 teams
such
as:
 In
2004,
DGC
goals
were
simple:
  PID
controllers
 Let
the
Naviga>on
system
take
the
car
 to
the
end.
  Kalman
Filters
 Higher
level
func,ons
were
irrelevant
  Obstacle
Avoidance
 10
–
20%
of
team
capacity
was
 because
basic
sensing
and
naviga,on
 spent
integra,ng
actuators.

 technologies
needed
to
be
developed.

  22. 22. 2005 DGC Landscape of Technologies 5
–
10%
of
team
capacity
was
spent
 30
‐
50%
of
team
capacity
 on
collec,ng
GPS
data.

 was
spent
enabling
mobile
 sensing
technologies.
 Mature
and
well‐established
high
 performance
GPS
market
enabled
 e Mobi rformanc nsing developers
to
focus
on
higher‐level
 Prevalent
Technologies:
 func,on
of
GPS
waypoint
traversal.

 le Se  SICK
 Prevalent
Technologies:
 Basic Awareness Pe  BOSCH
  NAVCOM
 High  Custom
Vision
Solu,ons
 Goal  Arrow
 Logic  Trimble
 40
–
60%
of
team
capacity
spent
 wri,ng
the
same
“commodity”
 Execution naviga,onal
algorithms
as
other
 teams
such
as:
 In
2005,
DGC
goals
were
s,ll
simple:
  PID
controllers
 Let
the
Naviga>on
system
take
the
car
 to
the
end.
  Kalman
Filters
 The
2005
DGC
was
effec,vely
the
  Obstacle
Avoidance
 10
–
20%
of
team
capacity
was
 conclusion
of
the
2004
DGC.
 spent
integra,ng
actuators.
¹
 ¹ Actuator integration will continue to be studied. It has sparked a market for turnkey actuator systems for vehicles. It is outside the scope of this presentation.
  23. 23. 2007 DUC Landscape of Technologies 5
–
10%
of
team
capacity
was
spent
 5
‐
15%
of
team
capacity
 on
collec,ng
GPS
data.

 was
spent
enabling
mobile
 sensing
technologies.
 Mature
and
well‐established
high
 performance
GPS
market
enabled
 e Allowed
more
capacity
to
 Mobi rformanc nsing developers
to
focus
on
higher‐level
 be
spent
on
higher
level
 func,on
of
GPS
waypoint
traversal.

 func,ons.
 le Se Prevalent
Technologies:
 Basic Awareness Prevalent
Enabling
 Pe Technologies:
  NAVCOM
 High Goal  Velodyne
  Arrow
 Logic  ibeo
  Trimble
 40
–
70%
of
team
capacity
 20
–
40%
of
team
capacity
spent
 was
spent
on
codifying
 wri,ng
the
same
“commodity”
 domain
knowledge
of
rules
 Execution naviga,onal
algorithms
as
other
 of
the
road:
 teams
such
as:
 Respect
rules
of
four‐way
  PID
controllers
 intersec>ons.
  Kalman
Filters
 Merge
safely
with
moving
 traffic.
  Obstacle
Avoidance
 10
–
20%
of
team
capacity
was
 Safely
pass
into
oncoming
 spent
integra,ng
actuators.
¹
 traffic.
 ¹ Actuator integration will continue to be studied. It has sparked a market for turnkey actuator systems for vehicles. It is outside the scope of this presentation.
  24. 24. Market beats Global Meltdown expectations Biggest.bubble.ever Nuke York Utopia End of Humanity Sameness  Badness Goodness 
  25. 25. Listen up humans. SciVestor provides research and consulting on emerging technologies that will change the world. I <3 those guys scivestor.com/insight twitter.com/jonaslamis Image (cc) http://www.flickr.com/photos/maxkiesler/2240153169/

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