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A Cloud-Based Bayesian Smart
Agent Architecture
for Internet-of-Things Applications
Authors: Veselin Pizurica, Piet Vandae...
IoT early years (technology) view
• IoT was about devices, protocols and data flows
• “gateway centric”
• “Liner logic”: l...
IoT today: business point of view
• You see marketing departments taking over 
• Picture more fuzzy, devices and services...
Connecting dots
“Swarm Intelligence”
Logic in a gateway
“Fog” computing
Logic in the cloud
Conway's Game of Life,
Nash gam...
Why NOT intelligence in the cloud?
• Latency
• Failure (in)tolerance (lack of redundancy) – general issue
in internet, add...
Why intelligence in the cloud?
• Device-agnostic and decouples logic from the
presentation layer
• Combination of the sens...
A Cloud-Based Smart Agent
Sense
Transmit
Store
Analyze offline
PresentReason
Act
Artificial Intelligence provides us the f...
Rational Agent
* Russell S., Norvig P.: Artificial Intelligence A Modern Approach, Third Edition, Pearson (2014)
Rational ...
Agent architecture choices
• The choice for a particular type of agent logic is
influenced by the characteristics of the e...
Why Bayesian Networks in IOT?
• Environments that cannot be completely observed, i.e.
when not all aspects that could impa...
• Belief propagation algorithm was introduced by Judea Pearl, 1982
• Pearl was inspired by the paper of cognitive psycholo...
Example: Car diagnosis
• Initial evidence: car won't start
• Testable variables (green), “broken, so fix it” variables
(or...
Let’s focus on battery->lights
Power of casual modelling
Lights are on
Lights are off
Compactness (and correctness)
Decision trees
Flow charts
X Y Z
Cloud Smart
Agent Platform Environment
SW-defined
Sensors
Graph
Modeling
SW-defined
Actuators
Percepts
Actions
Physical Se...
Example: waylay platform
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A Cloud-Based Bayesian Smart Agent Architecture for Internet-of-Things Applications

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Conference on Cognitive IOT in Rome : "A Cloud-Based Bayesian Smart Agent Architecture for Internet-of-Things Applications"

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A Cloud-Based Bayesian Smart Agent Architecture for Internet-of-Things Applications

  1. 1. A Cloud-Based Bayesian Smart Agent Architecture for Internet-of-Things Applications Authors: Veselin Pizurica, Piet Vandaele @waylay Rome, 27/10/2014
  2. 2. IoT early years (technology) view • IoT was about devices, protocols and data flows • “gateway centric” • “Liner logic”: left devices, right services…
  3. 3. IoT today: business point of view • You see marketing departments taking over  • Picture more fuzzy, devices and services all over the place
  4. 4. Connecting dots “Swarm Intelligence” Logic in a gateway “Fog” computing Logic in the cloud Conway's Game of Life, Nash gaming theory TIT for TAT …
  5. 5. Why NOT intelligence in the cloud? • Latency • Failure (in)tolerance (lack of redundancy) – general issue in internet, adding more blocks system even less stable • Cost of pushing data in the cloud – Energy (battery) – Data storage (data can be of a huge volume) – SW cost of integration – Lack of standardization • Security concerns: Authentication/Authorization • Privacy concerns
  6. 6. Why intelligence in the cloud? • Device-agnostic and decouples logic from the presentation layer • Combination of the sensor data with API “economy” • Integrating multiple IoT vertical solutions • Cloud-capacity scales horizontally, while distributed HW often needs to be swapped when HW resources are no longer sufficient • Cloud intelligence also allows easy generation of analytics regarding the usage of the logic itself. Which rules fired and why? How often? • An architectural model arises where logic is built once together with a REST API
  7. 7. A Cloud-Based Smart Agent Sense Transmit Store Analyze offline PresentReason Act Artificial Intelligence provides us the framework and tools to go beyond trivial real-time decision and automation use cases for IoT. In this presentation, we present a cloud-based smart agent architecture for real-time decision taking in IoT applications
  8. 8. Rational Agent * Russell S., Norvig P.: Artificial Intelligence A Modern Approach, Third Edition, Pearson (2014) Rational Agent Architecture *
  9. 9. Agent architecture choices • The choice for a particular type of agent logic is influenced by the characteristics of the environment in which an agent needs to operate • Type of agents (using software language to express the logic): – ‘if-then-else’ constructs that are available in any programming language or rules engine – flowchart models – CEP (complex event processing) engines – Graph models (Markov, Bayesian nets)
  10. 10. Why Bayesian Networks in IOT? • Environments that cannot be completely observed, i.e. when not all aspects that could impact a choice of action are observable. • Unreliable, noisy or incomplete data or when domain knowledge is incomplete such that probabilistic reasoning is required • Use cases where the number of causes for a particular observation is so large, that it is nearly impossible to enumerate them explicitly • Well suited to model expert-knowledge together with knowledge that is retrieved from accumulated data • Use cases where there are asynchronous information flows
  11. 11. • Belief propagation algorithm was introduced by Judea Pearl, 1982 • Pearl was inspired by the paper of cognitive psychologist Rumelhart on how children comprehend text • Generalization of the Kalman’s algorithm • Became very popular after it was shown that the same computations are in turbo codes and the same principles in the Viterbi algorithm • Main idea: inference by local message passing among neighboring nodes The message can loosely be interpreted as “I (node i ) think that you (node j) are that much likely to be in a given state”. Belief propagation
  12. 12. Example: Car diagnosis • Initial evidence: car won't start • Testable variables (green), “broken, so fix it” variables (orange) • Hidden variables (gray) ensure sparse structure, reduce parameters
  13. 13. Let’s focus on battery->lights
  14. 14. Power of casual modelling Lights are on Lights are off
  15. 15. Compactness (and correctness) Decision trees Flow charts X Y Z
  16. 16. Cloud Smart Agent Platform Environment SW-defined Sensors Graph Modeling SW-defined Actuators Percepts Actions Physical Sensors IoT platforms Social media Location Open Data Big Data API economy REST API LOB apps Proposed architecture Vertical Specific End-user Interface
  17. 17. Example: waylay platform

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