Dalimir Orfanus (UiO + ABB Copr. Research), 15.11.2011 ... · In WSN is defined as technique to...

Data Fusion in Wireless Sensor Networks Dalimir Orfanus (UiO + ABB Copr. Research), 15.11.2011, Cyber Physical Systems

1st part : Introduction

© ABB Group November 16, 2011 | Slide 2

Agenda

§  Motivation (What it is and why do we need it?) §  Classification (What is the landscape) §  Methods (Helicopter view) §  Architecture and models (Satellite view) §  Summary

§  Nakamura, E. F.; Loureiro, A. A. F. & Frery, A. C. Information fusion for wireless sensor networks: Methods, models, and classifications ACM Comput. Surv., ACM, 2007, 39

§  + other “minor” sources

Agenda Motivation Classification Methods Architectures Summary


Motivation

§  Building/Home automation

§  Industrial applications

§  Surveillance

§  Animals monitoring

§  Weather monitoring

§  Space exploration

§  Military

§  …

Wireless Sensor Network Are Everywhere



Motivation

§  Tiny sensors left (remotely) unattended in harsh environments to autonomously perform various activities

§  Sensing, measuring, pre-processing, reporting…

§  Equipped with radio, processing unit, battery §  Deployed either randomly or fixed installations

What is Wireless Sensor Network?

Base station



Motivation

§  What is the living room/oceans temperature?

§  Which sensor has the “right” value?

§  What is the sensor value tolerance?

§  Is one measurement enough?

§  How many samples? §  How many sensors do we

really need?

§  Processing and interpreting data is the fundamental issue in WSN

Fundamental Issue in WSN



Motivation

§  How to “combine” mass data gathered in sensors in order to get more precise and relevant information

§  “Combination of multiple sources to obtain improved information”

§  Cheaper, greater, quality, accuracy, …

Data and Information Fusion

Sea surface temperatures taken from ATSR-2



Motivation Yet Another Reason For Fusion

§  Many “noisy” data → few “clean” data §  Less data to transfer over greater distances

§  Battery saving and WSN lifetime extension



Motivation

§  Data vs. information §  Fusion vs. integration §  Fusion vs. aggregation §  Sensor vs. multisensor

§  Any permutation of above

§  Terminology is not unified…

§  Depends on the origin §  System architecture §  Applications §  Methods §  Theories §  …

Terminology Con-fusion



Motivation

§  Data Fusion “==“ Information Fusion

§  “Data fusion is a formal framework in which are expressed means and tools for the alliance of data originating from different sources. It aims at obtaining information of greater quality; the exact definition of ‘greater quality’ will depend upon the application”

§  WALD, L. 1999. Some terms of reference in data fusion. IEEE Trans. Geosci. Remote Sens. 13, 3 (May), 1190–1193

§  “Multisensor integration is the synergistic use of information provided by multiple sensory devices to assist in the accomplishment of a task by a system; and multisensor fusion deals with the combination of different sources of sensory information into one representational format during any stage in the integration process”

§  Lou, R. C., Yih, C.-C., and Su, K. L. 2002. Multisensor fusion and integration: Approaches, applications, and future research directions. IEEE Sensors J. 2, 2 (April), 107–119.

Terminology “resolution”



Motivation

§  In WSN data aggregation == data fusion §  Ability so summarize §  Volume: Min, max, avg, … §  Accuracy

Terminology “resolution” cont’d Agenda Motivation Classification Methods Architectures Summary


Classification 1/3

§  Complementary §  To obtain piece of information that is more broader

§  Redundant §  To obtain confidence

§  Cooperative §  To obtain more complex information

Relationship Among The Sources



Classification 1/3

§  Complementary §  Creating feature maps

§  Redundant §  To get higher accuracy

(GPS + GLONASS + GALILEO)

§  To transmit less data

§  Cooperative §  Localization

Relationship Among The Sources - Examples



Classification 2/3

§  Low-level §  Signal (measurement) fusion §  Filter’s out noise from raw data

§  Medium-level §  Feature (attribute) level fusion §  Attributes or features are fused into feature maps

§  High-level §  Symbol or decision level fusion §  Combination of input symbols to obtain confident

decision

§  Multilevel §  Combination of various level of abstraction

Levels of Abstraction



Classification 3/3

§  Data → Feature → Decision

§  Data In → Data Out §  Raw data into raw data, more accurate

§  Feature In → Feature Out §  Improve/refine feature

§  Decision In → Decision Out §  Merging decisions

§  Data In → Feature Out §  Feature extraction

§  Feature In → Decision Out §  Generating symbolic representation or

decision

Input and Output

§  Low level

§  Medium level

§  High level

§  Multilevel



Methods For Fusing 1/7

§  Decision fusion §  Decision is taken based on perceived situation

§  Bayesian inference §  Dempster-Shafer inference §  Fuzzy logic §  Neural networks §  Abductive reasoning §  Semantic information fusion

Inference




§  Taken from the control theory §  Computation of the process state based on the single or

sequence of measurements

§  Maximum likehood (ML) §  Maximum A Posteriori (MAP) §  Least Squares §  Moving Average Filter §  Kalman Filter §  Particle Filter

Estimation




§  Feature = aspect of the environment

§  Occupancy grid §  Multidimensional representation of the environment §  Areas occupied/free by an object/s §  Traffic maps

§  Network scans §  Sort of resource/activity maps §  Geographical distribution of resources or activities §  Regions of WSN with low energy/high activity

Feature Maps




§  Concrete sensor §  Sampling physical state variable of interest

§  Abstract sensor §  Interval of values from concrete sensor

§  Reliable abstract sensor §  Interval that always contains real values of sensed

physical state §  Computed based on several abstract sensors

§  Fault-tolerant averaging §  Fault-tolerant interval function

Reliable Abstract Sensors




§  In WSN is defined as technique to overcome: §  Implosion: duplication of the single data §  Overlap: same thing observed by more sensors

§  The goal is to minimize volume of data necessary to transfer into a sink node

§  Some techniques §  Suppression : Discards duplicates §  Packing : Packs 2 MAC frames into 1 MAC frame

§  Really aggregation?

Aggregation




§  Reducing source information that it contains less bits §  Lossy §  Lossless

§  Classical compression algorithms §  Consider only data representation without semantic

§  WSN algorithms for compression §  Exploits spatial correlation among sensor nodes

§  Distributed source coding §  Coding by ordering

Compression




§  Fusing data from more sources can §  Increase data reliability (confidence) §  Lower probability of error

§  Sensing of real information from the environment §  Stochastic and difficult to estimate in advance §  Use of probabilistic quantifying techniques to process

and fuse data

Information Theory Approach



Architecture and models 1/3

§  Built around data abstraction during fusion process

Information-based models

HALL, D. L. AND LLINAS, J. 1997. An introduction to multi-sensor data fusion. Proc. IEEE 85, 1 (January), 6–23




§  Models focused on specifying activities that has to be performed during fusion

§  Sequence and execution of activities is explicitly modeled

§  Observe-orient-decide-act

Activity-based models




§  Similar to information based models but focused on roles rather than activities

Role-based models

KOKAR, M. M., BEDWORTH, M. D., AND FRANKEL, C. B. 2000. A reference model for data fusion systems. In Sensor Fusion: Architectures, Algorithms and Applications IV. SPIE, Orlando, FL, 191–202.



Summary Fusion gives answers

§  How many samples §  How often to sample §  How many sensors §  How to get the most accurate information about sensed

real-world state variable (often stochastic)



Summary

§  Provides §  Set of techniques/methods/tools §  Framework how techniques/methods/tools should be

combined §  Helps

§  Reduce volume of transferred data §  Reduce battery consumption and extending network’s

lifetime §  Better understanding of ongoing process in the

environment in order to take optimal decision how to response

Fusion also…


Dalimir Orfanus (UiO + ABB Copr. Research), 15.11.2011 ... · In WSN is defined as technique to...

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