Herein, a review of the recent sensing applications, which harness ML enabled smart sensor systems, is presented. First well-known ML algorithms implemented in smart sensor systems for practical sensing applications are discussed.

Dec 15, 2024 · Overparameterized deep feedforward neural networks demonstrated excellent accuracy and generalizability when trained on large sensor datasets, in line with recent theoretical machine learning findings.

As a powerful tool for advanced data processing, machine learning has become a core technique for novel sensor development, aiming to discover the hidden rules that control complex systems.

Jun 28, 2021 · In this Perspective, we discuss computational sensing with a focus on intelligent sensor system design. By leveraging inverse design and machine learning techniques, data acquisition...

Jul 13, 2021 · With the widespread proliferation of (miniaturized) sensing facilities and the massive growth and popularity of the field of machine learning (ML) research, new frontiers in automated sensor data analysis have been explored that lead to paradigm shifts in many application domains.

Dec 1, 2024 · In this tutorial, we guided you through the process of transforming raw sensor data into actionable insights using machine learning techniques. You learned how to collect and preprocess sensor data, train and deploy a machine learning model, and extract valuable insights from sensor data.

Aug 23, 2024 · In this editorial, I synthesize my observations for the use of ML and AI in sensing from my own research and from the papers submitted to the journal. 1. While it can appear to some that ML and AI is a relatively new field for sensing, it has roots in the field of chemometrics, which has been around for decades now and should be acknowledged.

Apr 17, 2025 · Soft sensors play a vital role in industrial process monitoring and control by estimating difficult-to-measure quality variables. While significant progress has been made in improving the accuracy of soft sensor models, challenges remain in ensuring their interpretability and stability in dynamic industrial environments. From a measurement science perspective, ensuring transparency and ...

We discuss the role of smart sensors in different fields and explore how ML and DL can be used to extract insights and improve the accuracy and reliability of sensor data. Finally, we discuss the future of smart sensors and the role that ML and DL will continue to play in their development and deployment. Need Help?

4 days ago · Accurate assessment of training status in team sports is crucial for optimising performance and reducing injury risk. This pilot study investigates the feasibility of using machine learning (ML) models to estimate oxygen uptake (VO2) with wearable sensors during team sports activities. Six healthy male team sports athletes participated …