Roadmap on signal processing for next generation measurement systems

Dimitris K. Iakovidis; Melanie Ooi; Ye Chow Kuang; Serge Demidenko; Alexandr Shestakov; Vladimir Sinitsin; Manus Henry; Andrea Sciacchitano; Stefano Discetti; Silvano Donati; Michele Norgia; Andreas Menychtas; Ilias Maglogiannis; Selina C. Wriessnegger; Luis Alberto Barradas Chacon; George Dimas; Dimitris Filos; Anthony H. Aletras; Johannes Töger; Feng Dong; Shangjie Ren; Andreas Uhl; Jacek Paziewski; Jianghui Geng; Francesco Fioranelli; Ram M. Narayanan; Carlos Fernandez; Christoph Stiller; Konstantina Malamousi; Spyros Kamnis; Konstantinos Delibasis; Dong Wang; Jianjing Zhang; Robert X. Gao

doi:10.1088/1361-6501/ac2dbd

Roadmap on signal processing for next generation measurement systems

Dimitris K. Iakovidis, Melanie Ooi, Ye Chow Kuang, Serge Demidenko, Alexandr Shestakov, Vladimir Sinitsin, Manus Henry, Andrea Sciacchitano, Stefano Discetti, Silvano Donati, Michele Norgia, Andreas Menychtas, Ilias Maglogiannis, Selina C. Wriessnegger, Luis Alberto Barradas Chacon, George Dimas, Dimitris Filos, Anthony H. Aletras, Johannes Töger, Feng DongShangjie Ren, Andreas Uhl, Jacek Paziewski, Jianghui Geng, Francesco Fioranelli, Ram M. Narayanan, Carlos Fernandez, Christoph Stiller, Konstantina Malamousi, Spyros Kamnis, Konstantinos Delibasis, Dong Wang, Jianjing Zhang, Robert X. Gao

Research output: Contribution to journal › Review article › peer-review

18 Scopus citations

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 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.

Original language	English (US)
Article number	012002
Journal	Measurement Science and Technology
Volume	33
Issue number	1
DOIs	https://doi.org/10.1088/1361-6501/ac2dbd
State	Published - Jan 2022

All Science Journal Classification (ASJC) codes

Instrumentation
Engineering (miscellaneous)
Applied Mathematics

Access to Document

10.1088/1361-6501/ac2dbd

Cite this

Iakovidis, D. K., Ooi, M., Kuang, Y. C., Demidenko, S., Shestakov, A., Sinitsin, V., Henry, M., Sciacchitano, A., Discetti, S., Donati, S., Norgia, M., Menychtas, A., Maglogiannis, I., Wriessnegger, S. C., Chacon, L. A. B., Dimas, G., Filos, D., Aletras, A. H., Töger, J., ... Gao, R. X. (2022). Roadmap on signal processing for next generation measurement systems. Measurement Science and Technology, 33(1), Article 012002. https://doi.org/10.1088/1361-6501/ac2dbd

@article{9e3a7358ca56492b953f153858776abd,

title = "Roadmap on signal processing for next generation measurement systems",

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 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.",

author = "Iakovidis, {Dimitris K.} and Melanie Ooi and Kuang, {Ye Chow} and Serge Demidenko and Alexandr Shestakov and Vladimir Sinitsin and Manus Henry and Andrea Sciacchitano and Stefano Discetti and Silvano Donati and Michele Norgia and Andreas Menychtas and Ilias Maglogiannis and Wriessnegger, {Selina C.} and Chacon, {Luis Alberto Barradas} and George Dimas and Dimitris Filos and Aletras, {Anthony H.} and Johannes T{\"o}ger and Feng Dong and Shangjie Ren and Andreas Uhl and Jacek Paziewski and Jianghui Geng and Francesco Fioranelli and Narayanan, {Ram M.} and Carlos Fernandez and Christoph Stiller and Konstantina Malamousi and Spyros Kamnis and Konstantinos Delibasis and Dong Wang and Jianjing Zhang and Gao, {Robert X.}",

note = "Publisher Copyright: {\textcopyright} 2021 The Author(s). Published by IOP Publishing Ltd",

year = "2022",

month = jan,

doi = "10.1088/1361-6501/ac2dbd",

language = "English (US)",

volume = "33",

journal = "Measurement Science and Technology",

issn = "0957-0233",

publisher = "IOP Publishing Ltd.",

number = "1",

}

Iakovidis, DK, Ooi, M, Kuang, YC, Demidenko, S, Shestakov, A, Sinitsin, V, Henry, M, Sciacchitano, A, Discetti, S, Donati, S, Norgia, M, Menychtas, A, Maglogiannis, I, Wriessnegger, SC, Chacon, LAB, Dimas, G, Filos, D, Aletras, AH, Töger, J, Dong, F, Ren, S, Uhl, A, Paziewski, J, Geng, J, Fioranelli, F, Narayanan, RM, Fernandez, C, Stiller, C, Malamousi, K, Kamnis, S, Delibasis, K, Wang, D, Zhang, J & Gao, RX 2022, 'Roadmap on signal processing for next generation measurement systems', Measurement Science and Technology, vol. 33, no. 1, 012002. https://doi.org/10.1088/1361-6501/ac2dbd

TY - JOUR

T1 - Roadmap on signal processing for next generation measurement systems

AU - Iakovidis, Dimitris K.

AU - Ooi, Melanie

AU - Kuang, Ye Chow

AU - Demidenko, Serge

AU - Shestakov, Alexandr

AU - Sinitsin, Vladimir

AU - Henry, Manus

AU - Sciacchitano, Andrea

AU - Discetti, Stefano

AU - Donati, Silvano

AU - Norgia, Michele

AU - Menychtas, Andreas

AU - Maglogiannis, Ilias

AU - Wriessnegger, Selina C.

AU - Chacon, Luis Alberto Barradas

AU - Dimas, George

AU - Filos, Dimitris

AU - Aletras, Anthony H.

AU - Töger, Johannes

AU - Dong, Feng

AU - Ren, Shangjie

AU - Uhl, Andreas

AU - Paziewski, Jacek

AU - Geng, Jianghui

AU - Fioranelli, Francesco

AU - Narayanan, Ram M.

AU - Fernandez, Carlos

AU - Stiller, Christoph

AU - Malamousi, Konstantina

AU - Kamnis, Spyros

AU - Delibasis, Konstantinos

AU - Wang, Dong

AU - Zhang, Jianjing

AU - Gao, Robert X.

PY - 2022/1

Y1 - 2022/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85120751336&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85120751336&partnerID=8YFLogxK

U2 - 10.1088/1361-6501/ac2dbd

DO - 10.1088/1361-6501/ac2dbd

M3 - Review article

AN - SCOPUS:85120751336

SN - 0957-0233

VL - 33

JO - Measurement Science and Technology

JF - Measurement Science and Technology

IS - 1

M1 - 012002

ER -

Roadmap on signal processing for next generation measurement systems

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this