DTC Project 8.5 “Intelligent Sensing”
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Transcript of DTC Project 8.5 “Intelligent Sensing”
Data Information FusionDefence Technology Centre
DTC Project 8.5“Intelligent Sensing”
Prof C.J.Harris and Prof N.M.WhiteDr D. Karatzas and Dr A. Chorti
University of SouthamptonSchool of Electronics and Computer Science
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
Teaching Old Sensors New Tricks
Intelligent Sensors are systems combining sensing elements and sophisticated processing in the sensor housing. They are able to process information locally and autonomously react to specific situations.
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
Redundancy of simple sensors is not always a good idea. In the
case of a catastrophic event they will all suffer the same damage. Intelligent Sensors on the other
hand can reconfigure themselves
Intelligent Sensors can go where
humans cannot
Humans use intuition to respond to a tricky situation. Intelligent Sensors can also respond in a
clever way!
It is desirable to employ Intelligent Sensors to keep
human beings away from hazardous situations
Advantages of Intelligent Sensors
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
INTELLIGENTSENSOR
(DTC Project 8.5)
DTC Project 8.5 investigated algorithms for optimal signal extraction from sensors in the context of an Intelligent Sensor Software Architecture
INTELLIGENT SENSOR(DTC Project 8.5)
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
INTELLIGENTSENSOR 1
(DTC Project 8.5)
SENSOR MANAGEMENT(DTC Project 8.1)
PERFORMANCE METRIC
DECISION / CONTROL
DATA FUSION SYSTEM
INTELLIGENT SENSOR N
(DTC Project 8.5)…
By processing information locally, the sensor management system (DTC Project 8.1) can assume higher confidence on reported data
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State of the Art Research
IEEE1451
BS7986
Few industry standards exist for Intelligent Sensors
IEEE 1451 defines low-level aspects of intelligent sensors and communication protocols
BS 7986 describes higher levelin-sensor processing but does not define algorithmic implementation details
DTC Project 8.5 covers this gap!
Maintains compatibility to existing industry standards
Formally defines a framework for Intelligent Sensors implementation
Investigated algorithmic approaches to tackle common issues of real-world applications
INTELLIGENT SENSOR(DTC Project 8.5)
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
INTELLIGENT SENSOR(DTC Project 8.5)
Intelligent Sensor Software Architecture
A generic, modular architecture was developed as an advantageous intelligent sensor implementation
The Project 8.5 Intelligent Sensor Software Architecture introduces the following functionality:
To self-validate sensor data and identify inconsistent inputsTo self-adjust to drift/bias effects usually caused by the sensing element ageing or poisoning
To communicate sensor’s condition to the sensor management level, so proper action can be taken
To adapt to environmental changesTo autonomously reconfigure in order to continue operation despite any sensor degradation
INTELLIGENT SENSOR(DTC Project 8.5)
• Self-validation• Self-adjustment to drift/bias• Communication of sensor’s condition• Adaptation to environmental changes• Autonomous reconfiguration
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
Intelligent Sensor
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Primary Measurand
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Environment Measurand #2
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Intelligent SensorControl
Module Messaging
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IEEE Sensor Identification
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Sensor Interface #1
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Modules are combined in a mix-and-match fashion to create specific Intelligent Sensor implementations that address real-life scenarios
A primary measurand, as well as any number of secondary environmental measurands can be monitored in parallel
The Sensor Interface modules are responsible to:
Communicate with the sensing element hardwareObtain measurements on demandPerform basic signal processing (linearisation, A/D conversion etc)
The Fault Detection modules:
Assess incoming data and produce an uncertainty valueCorrect incoming data if possibleIndicate how the above values were calculated
The Fault Detection modules can make use of theoretical sensor models provided by Sensor Model Provider modules, which:
Act as sensor model librariesCan select the best model to use at any given time
The outputs from each array of sensors are fused by Internal Fusion modules:
Generate a single value and uncertainty at each iterationFilter out inconsistent values
The fused measurements can be checked for drift/bias by a Drift Estimation & Compensation module:
Estimates different types of drift from historical dataCorrects for drift and updates the uncertainty value accordinglyMakes use of physical sensor models
All modules are bound together by the Intelligent Sensor Control module:
Communicates the final corrected measurement to higher processesEnsures compatibility with IEEE and BS standardsIs responsible for timing, messaging between modules etc.
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
Internal Fusion
Each module in the architecture addresses a distinct common issue of real life implementations
But,There is no single way to tackle each of these issues!
DTC Project 8.5 investigated alternative algorithmic implementations for each of the modules
Sensor Interface
Intelligent SensorControl
Drift Estimation &Compensation
FaultDetection
Sensor ModelProvider
1. Additive Drift #12. Additive Drift #23. Multiplicative Drift4. …
Available AlgorithmicImplementations
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Intelligent SensorPressure
Temperature
Sensor Interface
IntelligentSensorControl
Drift Estimation &Compensation
Sensor Interface
Sensor Interface
FaultDetection
FaultDetection
Sensor Model Provider
Sensor Model Provider
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As an example, we will see how the Intelligent Sensor Software Architecture of Project 8.5 can be used to implement an Intelligent Sensor featuring a piezoresistive pressure sensor as the primary sensing element
The piezoresistive pressure sensor is interfaced with the architecture through a Sensor Interface module
The Sensor Interface module feeds directly a Drift Estimation & Compensation module which corrects the input for additive and multiplicative drift using models provided by a Sensor Model Provider module
The physical model for the pressure sensor is dependent on temperature, and the Sensor Model Provider needs to know this information to select the appropriate model
We can use an array of two temperature sensors (not necessarily of the same type), which interface with the Intelligent Sensor through their own Sensor Interface modules
The output of each of these sensors is assessed by a Fault Detection module, which makes use of physical models supplied by Sensor Model Provider modules
The temperature measurements are fused by an Internal Fusion module, before passed to the Intelligent Sensor Control moduleThe Intelligent Sensor Control is responsible to communicate temperature information back to the pressure sensors’ Sensor Model Provider moduleFinally, the corrected pressure information is passed to the Intelligent Sensor Control to communicate to higher processes
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
Intelligent SensorPressure
Temperature
Sensor Interface
IntelligentSensorControl
Drift Estimation &Compensation
Sensor Interface
Sensor Interface
FaultDetection
FaultDetection
Sensor Model Provider
Sensor Model Provider
Sensor Model Provider
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Intelligent Sensor
Pressure
Temperature
Sensor Interface
IntelligentSensorControl
Drift Estimation &Compensation
Sensor Interface
Sensor Interface
FaultDetection
FaultDetection
Sensor Model Provider
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On the right appears a snapshot of Project 8.5’s Intelligent Sensor Demonstrator, showing the implementation described
The correspondence of the modules between the architectural design and the implementation is highlighted
The demonstrator is now shown in action. As new measurements become available, each module performs its own processing on the data
The estimated additive and multiplicative drift can be seen in the Drift Estimation & Compensation module
The Fault Detection modules identify outliers and remove their effects on the signal
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
Project’s 8.5 developed a low level Intelligent Sensor Software Architecture which is generic, modular, compliant with existing industry standards and can be used to implement any sensory application
Some of the key attributes of the Intelligent Sensor Software Architecture are:
Project 8.5’s Intelligent Sensor requires minimal maintenance and therefore minimal human intervention
Its modular character makes it easy to use through a mix-and-match fashion
It is trivial to upgrade individual modules without altering the overall implementation
For each module a number of alternative implementations are available to cover a variety of application specific needs
INTELLIGENT SENSOR(DTC Project 8.5)
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
The list of potential applications for Project 8.5’s research output is endless. Two characteristic examples stemming from active research projects in the University of Southampton are:
Potential ApplicationsPotential Applications
Biometric Keypad Southampton Artificial Hand
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
Potential ApplicationsBiometric Keypad Southampton Artificial Hand
Combines “Chip and PIN” technology with biometric keystroke recognition to identify or verify an individual
Intelligent Sensors can be introduced on each key (current implementation features 2 piezoelectic sensors behind each pad)
Range of real-life Applications:
Banking
Security Systems (access control)
A long-running project at the University of Southampton utilising state of the art sensor technology
Features 3 sensors on each fingertip: Force, Temperature and Slip
Relationship to Project 8.5:
Introduce Intelligent Sensors on its fingertips
Reduce cabling requirements
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
D. Karatzas, A. Chorti, C.J. Harris and N.M. White, “Teaching Old Sensors New Tricks: Archetypes of Intelligence”, accepted at IEEE Sensors journal (Special Issue on Intelligent Sensors)
A. Chorti, D. Karatzas, N.M. White and C.J. Harris, “Use of the EKF for state dependent drift estimation in weakly nonlinear sensors” accepted at Sensors Letters
A. Chorti, D. Karatzas, N.M. White and C.J. Harris, “Intelligent Sensors in Software: The Use of Parametric Models for Phase Noise Analysis”, submitted to ICISIP 2006 conference on Intelligent Sensing and Information Processing, IEEE
N.M. White and P.J. Boltryk, “Advances in Intelligent Sensors”, book chapter, to appear in “Adaptronics”, Springer
P.J. Boltryk, C.J. Harris and N.M. White, “Intelligent Sensors – a generic software approach”, Sensors & their Applications XIII, University of Greenwich at Medway, Chatham Maritime, Kent, September 2005
P.J. Boltryk, C.J. Harris and N.M. White, “An Algorithmic Approach to the Optimal Extraction of Signals from Intelligent Sensors”, Nanotech 2005, Anaheim, USA, May 8-12, 2005
N.M. White, “Intelligent Sensors, Systems or Components?”, Invited Paper, Nanotech 2005, Anaheim USA, May 8-12, 2005
Publications
Data Information Fusion Defence Technology CentreProject 8.5 Intelligent Sensing
Contact DetailsAddress University of Southampton
School of Electronics and Computer ScienceRoom 1001, Building 86Southampton, SO17 1BJ
Telephone +44 (2380) 599204
Website www.dtc.soton.ac.uk
Prof N.M.White [email protected] C.J.Harris [email protected] D.Karatzas [email protected] A.Chorti [email protected]