Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor Systems

The emergence of novel sensing elements, computing nodes, wireless communication and integration technology provides unprecedented possibilities for the design and application of intelligent systems. Each new application system must be designed from scratch, employing sophisticated methods ranging f...

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Main Authors: Andreas König, Kuncup Iswandy
Format: Article
Language:English
Published: MDPI AG 2009-11-01
Series:Algorithms
Subjects:
Online Access:http://www.mdpi.com/1999-4893/2/4/1368/
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spelling doaj-3d04731db6354cd19ccf984efc2019672020-11-25T00:35:00ZengMDPI AGAlgorithms1999-48932009-11-01241368140910.3390/a2041368Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor SystemsAndreas KönigKuncup IswandyThe emergence of novel sensing elements, computing nodes, wireless communication and integration technology provides unprecedented possibilities for the design and application of intelligent systems. Each new application system must be designed from scratch, employing sophisticated methods ranging from conventional signal processing to computational intelligence. Currently, a significant part of this overall algorithmic chain of the computational system model still has to be assembled manually by experienced designers in a time and labor consuming process. In this research work, this challenge is picked up and a methodology and algorithms for automated design of intelligent integrated and resource-aware multi-sensor systems employing multi-objective evolutionary computation are introduced. The proposed methodology tackles the challenge of rapid-prototyping of such systems under realization constraints and, additionally, includes features of system instance specific self-correction for sustained operation of a large volume and in a dynamically changing environment. The extension of these concepts to the reconfigurable hardware platform renders so called self-x sensor systems, which stands, e.g., for self-monitoring, -calibrating, -trimming, and -repairing/-healing systems. Selected experimental results prove the applicability and effectiveness of our proposed methodology and emerging tool. By our approach, competitive results were achieved with regard to classification accuracy, flexibility, and design speed under additional design constraints. http://www.mdpi.com/1999-4893/2/4/1368/intelligent multi-sensor systemsauto-configurationresource-awarenesslean systemssensor signal processingcomputational modelingevolutionary computationself-x-systems
collection DOAJ
language English
format Article
sources DOAJ
author Andreas König
Kuncup Iswandy
spellingShingle Andreas König
Kuncup Iswandy
Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor Systems
Algorithms
intelligent multi-sensor systems
auto-configuration
resource-awareness
lean systems
sensor signal processing
computational modeling
evolutionary computation
self-x-systems
author_facet Andreas König
Kuncup Iswandy
author_sort Andreas König
title Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor Systems
title_short Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor Systems
title_full Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor Systems
title_fullStr Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor Systems
title_full_unstemmed Methodology, Algorithms, and Emerging Tool for Automated Design of Intelligent Integrated Multi-Sensor Systems
title_sort methodology, algorithms, and emerging tool for automated design of intelligent integrated multi-sensor systems
publisher MDPI AG
series Algorithms
issn 1999-4893
publishDate 2009-11-01
description The emergence of novel sensing elements, computing nodes, wireless communication and integration technology provides unprecedented possibilities for the design and application of intelligent systems. Each new application system must be designed from scratch, employing sophisticated methods ranging from conventional signal processing to computational intelligence. Currently, a significant part of this overall algorithmic chain of the computational system model still has to be assembled manually by experienced designers in a time and labor consuming process. In this research work, this challenge is picked up and a methodology and algorithms for automated design of intelligent integrated and resource-aware multi-sensor systems employing multi-objective evolutionary computation are introduced. The proposed methodology tackles the challenge of rapid-prototyping of such systems under realization constraints and, additionally, includes features of system instance specific self-correction for sustained operation of a large volume and in a dynamically changing environment. The extension of these concepts to the reconfigurable hardware platform renders so called self-x sensor systems, which stands, e.g., for self-monitoring, -calibrating, -trimming, and -repairing/-healing systems. Selected experimental results prove the applicability and effectiveness of our proposed methodology and emerging tool. By our approach, competitive results were achieved with regard to classification accuracy, flexibility, and design speed under additional design constraints.
topic intelligent multi-sensor systems
auto-configuration
resource-awareness
lean systems
sensor signal processing
computational modeling
evolutionary computation
self-x-systems
url http://www.mdpi.com/1999-4893/2/4/1368/
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