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, Francesco Fioranelli, More Authors

*Corresponding author for this work

Research output: Contribution to journalReview articleScientificpeer-review

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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
Article number012002
Pages (from-to)1-48
Number of pages48
JournalMeasurement Science and Technology
Volume33
Issue number1
DOIs
Publication statusPublished - 2021

Keywords

  • signal processing
  • measurement systems
  • optical measurements
  • machine learning
  • biomedical applications
  • environmental applications
  • industrial applications
  • Biomedical applications
  • Environmental applications
  • Industrial applications
  • Measurement systems
  • Machine learning
  • Optical measurements
  • Signal processing

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