next step in sensor networks
TRANSCRIPT
Next Step in Sensor Networks
Design of intelligent systems Martin van Rijn
May 29, 2012
Boston Livonia
Brussel
Delft
Qatar
Coventry
Frankfurt
Stuttgart
Nogent s/
Marne Wheelers Hill Bangalore
Seoul
Shanghai
Yokohama
Tokyo
Martin van Rijn
Intelligente Sensor Netwerken
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TNO in de world
Martin van Rijn
Intelligent Sensor Networks
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Groningen
Eindhoven
Den Helder
Den Haag
Rijswijk
Delft
Apeldoorn
Leiden
Enschede
Hoofddorp
Utrecht
Soesterberg
Zeist
Helmond
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Intelligente Sensor Netwerken
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TNO in the Netherlands
Martin van Rijn
Intelligent Sensor Networks
Martin van Rijn
Intelligente Sensor Netwerken
May 29, 2012
Kennis-
ontwikkeling
Kennis-
toepassing
Kennis-
exploitatie
Ontwikkelen
fundamentele
kennis
Samen
met universiteiten
Samen
met partners
Samen
met klanten
Verankeren
in de markt
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TNO Activities
Martin van Rijn
Intelligent Sensor Networks
Martin van Rijn
Intelligente Sensor Netwerken
May 29, 2012
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TNO Theme’s
Martin van Rijn
Intelligent Sensor Networks
Martin van Rijn
Intelligent Sensor Networks
TNO and Intelligent Sensor Network Research
Adaptive Multi Sensor Networks
Enabling Technology / 2011 – 2014
lange termijn onderzoek (>3 jaar)
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Everything get’s connected…
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Intelligent Sensor Networks
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Martin van Rijn
Intelligent Sensor Networks
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Everything get’s connected…
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Intelligent Sensor Networks
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Everything get’s connected…
Martin van Rijn
Intelligent Sensor Networks
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Everything get’s
connected…
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Intelligent Sensor Networks
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The proof of the pudding is in the eating
Martin van Rijn
Intelligent Sensor Networks
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The proof of the pudding is in the eating
Martin van Rijn
Intelligent Sensor Networks
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The proof of the pudding is in the eating
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Intelligent Sensor Networks
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The proof of the pudding is in the eating
Integrating different research domains
System properties
From design-time to run-time optimization
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Intelligent Sensor Networks
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Design Challenges
Martin van Rijn
Intelligent Sensor Networks
Sensor Fusion
(Wireless)
Sensor Networks
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Design Challenges
Multi Agent Systems
Intelligent
Systems Complex Systems
Self-Adaptive
Hierarchical
Complex Systems
Cognitive
Intelligent
Autonomous
Swarming
Agile
Network enabled
Dynamic
Cyber Physical
Cyber
Learning
Ubiquitous
Robust
Big Data
Self-Organizing
Hybrid
System scalability in users, time, sensors and functions
System robustness despite changing quality and availability of
sensor observations, communication, computation and energy
System adaptivity: optimization of information generation processes
regarding the valid information need
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Intelligent Sensor Networks
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Design Challenges
Adaptive
Robust Scalable
Martin van Rijn
Intelligent Sensor Networks
From design-time optimization….
To run-time optimization
*Situation = System + Environment
System
Element
Element
Element
Pre defined
required results
System
Element
Element
Element
Best possible
results given the
valid situation*
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Design Challenges
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Intelligent Sensor Networks
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Design Approach
Hostile Environment
Asymmetric Hostile System
Symmetric Hostile System
Symmetric Hostile System
Asymmetric Hostile System
Friendly Environment
The System
Neutral Environment
Neutral System
Friendly System
Neutral System
Friendly System
Three basic steps in design of an intelligent system:
System model, functional components
Information hierarchy and cardinality
System evaluation and optimization (run-time)
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Intelligent Sensor Networks
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Design Approach
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Intelligent Sensor Networks
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Design Approach
Sensing is intimately
related with acting
0
Hie
rarc
hy
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Intelligent Sensor Networks
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Design Approach
• Reaction time,
• Spatial distribution or
• Information abstraction (JDL)
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Intelligent Sensor Networks
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Design Approach
Evaluation of added value:
Reward = Value – Cost
Absolute:
R ≥ 0 then action is executed
(sensing as well as acting)
Relative:
R1 > R2
R of action 1 is higher
then R of action 2 so
action 1 is executed
Or
V/C - Optimizing Value
per Cost Unit. Action with
highest Value per Cost Unit
is executed
Evaluation / optimization processes