Roadmap on Signal Processing for Next Generation Measurement Systems

TL;DR

This paper provides a comprehensive overview of current and future signal processing techniques for next-generation measurement systems, emphasizing AI-driven methods and highlighting research challenges and opportunities across various scientific fields.

Contribution

It offers a critical, organized roadmap of state-of-the-art signal processing methods and applications, guiding future research and funding directions.

Findings

AI and machine learning are transforming signal processing.

Next-generation systems require advanced, integrated signal analysis techniques.

The roadmap identifies key challenges and opportunities for future research.

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.