Artificial intelligence (AI)-based methods are rapidly advancing the development of sensor technology, bringing about significant advancements for sensors in structural design/optimization, fabrication, calibration and application. The recent involvement of AI models has provided a new paradigm for the calibration of sensors and greatly improved the accuracy and stability of obtained sensing characteristics. In this paper, we present an overview of the advances of AI methods in sensor calibration in recent years. The superiority of leveraging AI models in getting the transfer function, compensating for ambient interferences/drifts, and promoting large-scale, low-cost sensors is reviewed and discussed to illustrate the pioneering transformations in this domain. Relevant enhancing tools for data preprocessing, training optimization and data augmentation are also mentioned. The significant achievements in various sensing systems have demonstrated that AI methods can be a powerful solution to the critical issues in calibrating sensors. However, there are still several critical challenges persisting alongside these remarkable achievements, and long-term commitment remains essential for future investigations.
Kou et al. (Thu,) studied this question.