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Roadmap on signal processing for next generation measurement systems

Iakovidis, Dimitris K. ; Ooi, Melanie ; Kuang, Ye Chow ; Demidenko, Serge ; Shestakov, Alexandr ; Sinitsin, Vladimir ; Henry, Manus ; Sciacchitano, Andrea ; Discetti, Stefano and Donati, Silvano , et al. (2022) In Measurement Science and Technology 33(1).
Abstract

Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to... (More)

Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Biomedical applications, Environmental applications, Industrial applications, Machine learning, Measurement systems, Optical measurements, Signal processing
in
Measurement Science and Technology
volume
33
issue
1
article number
012002
publisher
IOP Publishing
external identifiers
  • scopus:85120751336
ISSN
0957-0233
DOI
10.1088/1361-6501/ac2dbd
language
English
LU publication?
yes
id
4cb57824-a5d7-4622-80c8-7cd82598fb7b
date added to LUP
2022-12-29 09:22:07
date last changed
2023-10-12 14:45:35
@article{4cb57824-a5d7-4622-80c8-7cd82598fb7b,
  abstract     = {{<p>Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.</p>}},
  author       = {{Iakovidis, Dimitris K. and Ooi, Melanie and Kuang, Ye Chow and Demidenko, Serge and Shestakov, Alexandr and Sinitsin, Vladimir and Henry, Manus and Sciacchitano, Andrea and Discetti, Stefano and Donati, Silvano and Norgia, Michele and Menychtas, Andreas and Maglogiannis, Ilias and Wriessnegger, Selina C. and Chacon, Luis Alberto Barradas and Dimas, George and Filos, Dimitris and Aletras, Anthony H. and Töger, Johannes and Dong, Feng and Ren, Shangjie and Uhl, Andreas and Paziewski, Jacek and Geng, Jianghui and Fioranelli, Francesco and Narayanan, Ram M. and Fernandez, Carlos and Stiller, Christoph and Malamousi, Konstantina and Kamnis, Spyros and Delibasis, Konstantinos and Wang, Dong and Zhang, Jianjing and Gao, Robert X.}},
  issn         = {{0957-0233}},
  keywords     = {{Biomedical applications; Environmental applications; Industrial applications; Machine learning; Measurement systems; Optical measurements; Signal processing}},
  language     = {{eng}},
  number       = {{1}},
  publisher    = {{IOP Publishing}},
  series       = {{Measurement Science and Technology}},
  title        = {{Roadmap on signal processing for next generation measurement systems}},
  url          = {{http://dx.doi.org/10.1088/1361-6501/ac2dbd}},
  doi          = {{10.1088/1361-6501/ac2dbd}},
  volume       = {{33}},
  year         = {{2022}},
}