A Cloud-Based Bayesian Smart Agent Architecture

for Internet-of-Things Applications

Authors: Veselin Pizurica, Piet Vandaele @waylay

Rome, 27/10/2014

IoT early years (technology) view

• IoT was about devices, protocols and data flows• “gateway centric”• “Liner logic”: left devices, right services…

IoT today: business point of view

• You see marketing departments taking over • Picture more fuzzy, devices and services all over the

place

Connecting dots

“Swarm Intelligence”

Logic in a gateway“Fog” computing

Logic in the cloud

Conway's Game of Life,Nash gaming theoryTIT for TAT …

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

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

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

Rational Agent

* Russell S., Norvig P.: Artificial Intelligence A Modern Approach, Third Edition, Pearson (2014)

Rational Agent Architecture *

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)

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

• 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

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

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-definedSensors

Graph Modeling

SW-definedActuators

Percepts

Actions

Physical Sensors

IoT platforms

Social media

Location

Open Data

Big Data

API economy

REST API

LOB apps

Proposed architecture

VerticalSpecificEnd-userInterface

Example: waylay platform