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 journalReview articlepeer-review

12 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 languageEnglish (US)
Article number012002
JournalMeasurement Science and Technology
Volume33
Issue number1
DOIs
StatePublished - Jan 2022

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Engineering (miscellaneous)
  • Applied Mathematics

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