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.
Cite
@article{arxiv.2111.02493,
title = {Roadmap on Signal Processing for Next Generation Measurement Systems},
author = {D. K. Iakovidis and M. Ooi and Y. C. Kuang and S. Demidenko and A. Shestakov and V. Sinitsin and M. Henry and A. Sciacchitano and A. Discetti and S. Donati and M. Norgia and A. Menychtas and I. Maglogiannis and S. C. Wriessnegger and L. A. Barradas Chacon and G. Dimas and D. Filos and A. H. Aletras and J. Töger and F. Dong and S. Ren and A. Uhl and J. Paziewski and J. Geng and F. Fioranelli and R. M. Narayanan and C. Fernandez and C. Stiller and K. Malamousi and S. Kamnis and K. Delibasis and D. Wang and J. Zhang and R. X. Gao},
journal= {arXiv preprint arXiv:2111.02493},
year = {2022}
}
Comments
48 pages, https://iopscience.iop.org/article/10.1088/1361-6501/ac2dbd