The concept of a reference model has been well known in the communications

industry for many years. This has provided clearly defined layers and interface standards

which allow different organisations and across the industry to develop products independent

of each other in the knowledge that their products will function correctly within the greater

system. With the move towards massively parallel sensor systems networks, a similar

approach needs to be adopted in order to permit concurrent developments in sensor

networks. This paper summarises the need for such a reference model, and proposes a

reference model applicable to sensor system

Bremner, Duncan

English

Enlighten: Publications

,nn 
 
 
 
 
Bremner, D. (2011) Sensor systems: a hierarchical approach. Project 
Report. Scottish Sensor Systems Centre. 
Copyright © 2011 The Author 
 
A copy can be downloaded for personal non-commercial research or study, 
without prior permission or charge 
 
Content must not be changed in any way or reproduced in any format 
or medium without the formal permission of the copyright holder(s) 
 
 
 
 
http://eprints.gla.ac.uk/104909/ 
 
 
 
  Deposited on:  10 April 2015 
 
 
 
 
 
 
 
 
 
 
 
 
 
Enlighten – Research publications by members of the University of Glasgow 
http://eprints.gla.ac.uk 
 www.sensorsystems.org.uk 
 
Page 1 of 5 
www.sensorsystems.org.uk 
Sensor systems: a hierarchical approach  
Duncan Bremner,    University of Glasgow 
 
Abstract. The concept of a reference model has been well known in the communications 
industry for many years. This has provided clearly defined layers and interface standards 
which allow different organisations and across the industry to develop products independent 
of each other in the knowledge that their products will function correctly within the greater 
system. With the move towards massively parallel sensor systems networks, a similar 
approach needs to be adopted in order to permit concurrent developments in sensor 
networks. This paper summarises the need for such a reference model, and proposes a 
reference model applicable to sensor system. 
 
Background.  
In the 1980’s the telecommunications industry recognised that the network and equipment 
complexity was giving rise to the breakdown of the conventional, vertically integrated 
equipment companies in favour of specialist companies focusing on particular components 
required within the overall system. In order to enable the industry to develop effectively, the 
CCITT, the Geneva based telecoms standards body defined a seven layer reference model 
with clearly defined functions and interfaces within and between each layer. This model, 
known as the Open Systems Interconnect (OSI) model and enabled the rapid expansion of 
the communications industry which culminated in the realisation of the internet. 
 
Layer 7
Layer 6
Layer 5
Layer 4
Layer 3
Layer 2
Layer 1
Application Layer
Presentation Layer
Session Layer
Transport Layer
Network Layer
Data Link Layer
Physical Layer
Layer 7
Layer 6
Layer 5
Layer 4
Layer 3
Layer 2
Physical Link
Layer 1
 
Figure 1  OSI Reference Model 
 
With the advent of high performance, low power processing and communication platforms, it 
is now possible to develop complex sensor systems that integrate many different sensor 
technologies into a sensor  system. However, in order to enable concurrent developments 
 www.sensorsystems.org.uk 
 
Page 2 of 5 
www.sensorsystems.org.uk 
and maintain interoperability across the range of activities and requirements in a complex 
system, it is proposed that a reference model be developed. Using the approach taken by the 
successful OSI model, a comparable model for a hierarchical sensor system is proposed. 
 
A sensor systems reference model 
As in the case of communication systems, a sensor system is now more complex than can 
be effectively produced by a single, vertically integrated organisation. Consequently, the 
component parts and functions of sensor system need to be delineated by function and 
interface in order that concurrent system development can take place efficiently. The 
derivation of the model is based upon the OSI model but adapted for the specialist 
requirements of a complex sensor system. By examining the fundamental requirements of a 
sensor system, it can be established that all sensor systems carry out the same functions. In 
all cases, there is a requirement to detect a parametric change in the measureand, and after 
suitable conversion of the data into information, to pass that information to a ‘decision 
making authority’.  
 
Importantly, although the sensor system may carry out signal pre-processing or filtering, it 
does not make any decisions; this is beyond the remit of a sensor system. In the case of 
complex networks, this decision authority is often a human being, however it may be a 
machine system such as a automotive engine management system.  
 
 
Po
w
er
 
an
d 
m
an
ag
em
en
t 
Sensor Element 
Transductance & pre-processing
Communications and networking
Data repository
Analysis & post processing
Visualisation & presentation
Measurand
Superior decision system (human, biological, electronic, 
mechanical, chemical) acting upon the sensor system output 
D
at
a
In
fo
rm
at
io
n
Po
w
er
 
an
d 
m
an
ag
em
en
t 
D
at
a
In
fo
rm
at
io
n
 
Figure 2   Sensor Systems Hierarchy 
 
Using this generic approach, the model can be applied to a simple sensor system such as a 
thermometer or weather vane, or a highly complex network such as a battlefield 
management system or traffic management system. In order to understand the logic in 
 www.sensorsystems.org.uk 
 
Page 3 of 5 
www.sensorsystems.org.uk 
developing this proposed Sensor Systems Stack, an explanation of the different layers 
follows. 
 
 
 
 
 
This is the foundation element of the stack and is responsible for the detection and 
measurement of the quantity in question.  The elements operate in different ways depending 
on the type of sensor but are usually sensitive to a change in energy within the measurand 
causing a phenomenological change. This change in energy of the measurand gives rise to a 
secondary energy change (chemical, optical, nuclear, mechanical, electro-magnetic etc) 
within the sensor which is used to indicate the presence or absence of the quantity under 
test.  
 
 
 
 
 
Transductance is usual in a sensor device in order to convert the energy change produced 
by the sensor element into energy suitable for use. In modern sensor networks this is 
normally electrical energy although it may be another form; a simple example being a 
traditional mercury thermometer. Although the mercury is an effective visual indicator, it is 
difficult to transmit the positional information to a remote location.  A second and important 
requirement of the transductance stage is that of signal conditioning and logging. In many 
cases the logging is based upon a time stamp but the measurement may be logged against 
another parameter such as temperature or pressure. Pre-conditioning may be functions such 
as removal of noise or distortion from the signal but also may be a function of the parameter 
such as exceeding a minimum threshold.  
 
 
 
 
The communication layer transports the captured sensor data from the location of the 
measurement to a storage location. In simple sensors, this communication is often one way; 
from the sensor to the storage location. However in advanced sensor devices, duplex 
communication protocols are used; sensor -> data store, and pre-condition rules - > sensor.  
Selection of the communication protocol and the sensor network architecture can have 
significant effects on the power demand of the network and careful consideration should be 
given to the performance trade-offs associated with this area. 
 
 
 
 
 
Sensor Element  
Transductance & pre-processing 
Communications and networking 
 www.sensorsystems.org.uk 
 
Page 4 of 5 
www.sensorsystems.org.uk 
 
 
 
In any sensor system the storage of the raw data obtained from the sensor elements is 
essential in order to carry out post processing operations and trend analysis. In the case of 
simple sensor devices  this can be a relatively modest data storage location, however if the 
sensing elements are recording video information, the storage and categorisation of this 
information can present significant complexities.  Data reduction techniques are important in 
reducing the total storage requirements however, in the case of retrospective analysis to 
identify trends.   
 
 
 
 
 
Although the data repository contains data, decisions can only be made on information. The 
analysis and post processing function is responsible for the conversion of the measured data 
retrieved from the sensor elements into meaningful data upon which a decision may be 
made. The important difference between data and information is the introduction of context. 
A piece of data indicating a temperature of 35 C does not, in itself convey any information. 
This could indicate a hot day, a warm electronic component, or a water temperature a 
considerable distance from the boiling point. Only when it is placed in context, in this case a 
monitor of a patient’s temperature can a decision be made that this indicates a very cold 
patient. In addition to converting data into information, this function is also responsible for 
post processing such as filtering, integrating or averaging such that additional information 
can be derived from the system. 
 
 
 
 
 
The highest function within a sensor system is the processing of the information into a 
manner which can be understood by the superior decision system. In the case of a human 
operation this is likely to be presented in a manner which will stimulate one of our senses; in 
many cases sight or hearing. However, if the superior decision system is a control system, 
the correct presentation of the data may be in the form of an error message or a signal 
voltage. In the case of a complex sensor system such as a battlefield information system of a 
traffic control system, the intelligible presentation of the information can present as many 
challenges as the gathering of the original data. Considerable research has been undertaken 
to quantify the problems associated with data overload of critical operators such as aircraft 
pilots or vehicle drivers that demonstrates the benefit of effective data presentation. 
 
 
 
 
 
 
Data repository 
Analysis and post processing 
Visualisation and presentation 
 www.sensorsystems.org.uk 
 
Page 5 of 5 
www.sensorsystems.org.uk 
 
 
 
The final component of a sensor system is the power and management of the complete 
system. While researching sensor systems it was recognised that many previous attempts to 
analyse sensor systems identified power as a separate element within the stack 
components. However, it is suggested that this is incorrect as all the components of a sensor 
system can impact both the power consumption and the management capability of a system. 
Low power  sensors, even zero power (energy scavenging) devices do not, in themselves 
modify the fundamental data or information flow through the stack. Power consumption and 
system management, although important from overall system functional aspects, do not in 
themselves modify the absolute functionality of a system. 
Conclusion 
The establishment of the SSSC as a dedicated centre looking at the challenges of large and 
widely distributed sensor systems delivers an excellent opportunity to consider the holistic 
problems. Over the last decade, the development of portable and highly integrated sensor 
platforms; the Apple iPhone being an excellent example, has delivered the capability to 
gather vast amounts of data upon which to generate new insights into behaviour. It is hoped 
that the framework suggested in this paper will provide an initial reference upon which a 
more rigorous methodology can be developed when developing new sensor systems. 
Power and management 


Sensor systems: a hierarchical approach

Enlighten

,nn     Bremner, D. (2011) Sensor systems: a hierarchical approach. Project Report. Scottish Sensor Systems Centre. Copyright © 2011 The Author  A copy can be downloaded for personal non-commercial research or study, without prior permission or charge  Content must not be changed in any way or reproduced in any format or medium without the formal permission of the copyright holder(s)     http://eprints.gla.ac.uk/104909/      Deposited on:  10 April 2015              Enlighten – Research publications by members of the University of Glasgow http://eprints.gla.ac.uk  www.sensorsystems.org.uk  Page 1 of 5 www.sensorsystems.org.uk Sensor systems: a hierarchical approach  Duncan Bremner,    University of Glasgow  Abstract. The concept of a reference model has been well known in the communications industry for many years. This has provided clearly defined layers and interface standards which allow different organisations and across the industry to develop products independent of each other in the knowledge that their products will function correctly within the greater system. With the move towards massively parallel sensor systems networks, a similar approach needs to be adopted in order to permit concurrent developments in sensor networks. This paper summarises the need for such a reference model, and proposes a reference model applicable to sensor system.  Background.  In the 1980’s the telecommunications industry recognised that the network and equipment complexity was giving rise to the breakdown of the conventional, vertically integrated equipment companies in favour of specialist companies focusing on particular components required within the overall system. In order to enable the industry to develop effectively, the CCITT, the Geneva based telecoms standards body defined a seven layer reference model with clearly defined functions and interfaces within and between each layer. This model, known as the Open Systems Interconnect (OSI) model and enabled the rapid expansion of the communications industry which culminated in the realisation of the internet.  Layer 7Layer 6Layer 5Layer 4Layer 3Layer 2Layer 1Application LayerPresentation LayerSession LayerTransport LayerNetwork LayerData Link LayerPhysical LayerLayer 7Layer 6Layer 5Layer 4Layer 3Layer 2Physical LinkLayer 1 Figure 1  OSI Reference Model  With the advent of high performance, low power processing and communication platforms, it is now possible to develop complex sensor systems that integrate many different sensor technologies into a sensor  system. However, in order to enable concurrent developments  www.sensorsystems.org.uk  Page 2 of 5 www.sensorsystems.org.uk and maintain interoperability across the range of activities and requirements in a complex system, it is proposed that a reference model be developed. Using the approach taken by the successful OSI model, a comparable model for a hierarchical sensor system is proposed.  A sensor systems reference model As in the case of communication systems, a sensor system is now more complex than can be effectively produced by a single, vertically integrated organisation. Consequently, the component parts and functions of sensor system need to be delineated by function and interface in order that concurrent system development can take place efficiently. The derivation of the model is based upon the OSI model but adapted for the specialist requirements of a complex sensor system. By examining the fundamental requirements of a sensor system, it can be established that all sensor systems carry out the same functions. In all cases, there is a requirement to detect a parametric change in the measureand, and after suitable conversion of the data into information, to pass that information to a ‘decision making authority’.   Importantly, although the sensor system may carry out signal pre-processing or filtering, it does not make any decisions; this is beyond the remit of a sensor system. In the case of complex networks, this decision authority is often a human being, however it may be a machine system such as a automotive engine management system.    Power and management Sensor Element Transductance & pre-processingCommunications and networkingData repositoryAnalysis & post processingVisualisation & presentationMeasurandSuperior decision system (human, biological, electronic, mechanical, chemical) acting upon the sensor system output DataInformationPower and management DataInformation Figure 2   Sensor Systems Hierarchy  Using this generic approach, the model can be applied to a simple sensor system such as a thermometer or weather vane, or a highly complex network such as a battlefield management system or traffic management system. In order to understand the logic in  www.sensorsystems.org.uk  Page 3 of 5 www.sensorsystems.org.uk developing this proposed Sensor Systems Stack, an explanation of the different layers follows.      This is the foundation element of the stack and is responsible for the detection and measurement of the quantity in question.  The elements operate in different ways depending on the type of sensor but are usually sensitive to a change in energy within the measurand causing a phenomenological change. This change in energy of the measurand gives rise to a secondary energy change (chemical, optical, nuclear, mechanical, electro-magnetic etc) within the sensor which is used to indicate the presence or absence of the quantity under test.       Transductance is usual in a sensor device in order to convert the energy change produced by the sensor element into energy suitable for use. In modern sensor networks this is normally electrical energy although it may be another form; a simple example being a traditional mercury thermometer. Although the mercury is an effective visual indicator, it is difficult to transmit the positional information to a remote location.  A second and important requirement of the transductance stage is that of signal conditioning and logging. In many cases the logging is based upon a time stamp but the measurement may be logged against another parameter such as temperature or pressure. Pre-conditioning may be functions such as removal of noise or distortion from the signal but also may be a function of the parameter such as exceeding a minimum threshold.      The communication layer transports the captured sensor data from the location of the measurement to a storage location. In simple sensors, this communication is often one way; from the sensor to the storage location. However in advanced sensor devices, duplex communication protocols are used; sensor -> data store, and pre-condition rules - > sensor.  Selection of the communication protocol and the sensor network architecture can have significant effects on the power demand of the network and careful consideration should be given to the performance trade-offs associated with this area.      Sensor Element  Transductance & pre-processing Communications and networking  www.sensorsystems.org.uk  Page 4 of 5 www.sensorsystems.org.uk    In any sensor system the storage of the raw data obtained from the sensor elements is essential in order to carry out post processing operations and trend analysis. In the case of simple sensor devices  this can be a relatively modest data storage location, however if the sensing elements are recording video information, the storage and categorisation of this information can present significant complexities.  Data reduction techniques are important in reducing the total storage requirements however, in the case of retrospective analysis to identify trends.        Although the data repository contains data, decisions can only be made on information. The analysis and post processing function is responsible for the conversion of the measured data retrieved from the sensor elements into meaningful data upon which a decision may be made. The important difference between data and information is the introduction of context. A piece of data indicating a temperature of 35 C does not, in itself convey any information. This could indicate a hot day, a warm electronic component, or a water temperature a considerable distance from the boiling point. Only when it is placed in context, in this case a monitor of a patient’s temperature can a decision be made that this indicates a very cold patient. In addition to converting data into information, this function is also responsible for post processing such as filtering, integrating or averaging such that additional information can be derived from the system.      The highest function within a sensor system is the processing of the information into a manner which can be understood by the superior decision system. In the case of a human operation this is likely to be presented in a manner which will stimulate one of our senses; in many cases sight or hearing. However, if the superior decision system is a control system, the correct presentation of the data may be in the form of an error message or a signal voltage. In the case of a complex sensor system such as a battlefield information system of a traffic control system, the intelligible presentation of the information can present as many challenges as the gathering of the original data. Considerable research has been undertaken to quantify the problems associated with data overload of critical operators such as aircraft pilots or vehicle drivers that demonstrates the benefit of effective data presentation.       Data repository Analysis and post processing Visualisation and presentation  www.sensorsystems.org.uk  Page 5 of 5 www.sensorsystems.org.uk    The final component of a sensor system is the power and management of the complete system. While researching sensor systems it was recognised that many previous attempts to analyse sensor systems identified power as a separate element within the stack components. However, it is suggested that this is incorrect as all the components of a sensor system can impact both the power consumption and the management capability of a system. Low power  sensors, even zero power (energy scavenging) devices do not, in themselves modify the fundamental data or information flow through the stack. Power consumption and system management, although important from overall system functional aspects, do not in themselves modify the absolute functionality of a system. Conclusion The establishment of the SSSC as a dedicated centre looking at the challenges of large and widely distributed sensor systems delivers an excellent opportunity to consider the holistic problems. Over the last decade, the development of portable and highly integrated sensor platforms; the Apple iPhone being an excellent example, has delivered the capability to gather vast amounts of data upon which to generate new insights into behaviour. It is hoped that the framework suggested in this paper will provide an initial reference upon which a more rigorous methodology can be developed when developing new sensor systems. Power and management 

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