AI-Driven Sensing Technology: Review

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 10; p. 2958
• Main Authors: Chen, Long, Xia, Chenbin, Zhao, Zhehui, Fu, Haoran, Chen, Yunmin
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 07.05.2024
• Subjects: AI-driven sensing applications; Algorithms; Artificial intelligence; Biomedical engineering; Machine learning; ML/DL algorithm; Neural networks; performance enhancement; Robotics; sensing technology; Sensors; Signal processing; Technology application; Germany; AI-driven sensing applications; performance enhancement; sensing technology; ML/DL algorithm
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24102958

Machine learning and deep learning technologies are rapidly advancing the capabilities of sensing technologies, bringing about significant improvements in accuracy, sensitivity, and adaptability. These advancements are making a notable impact across a broad spectrum of fields, including industrial automation, robotics, biomedical engineering, and civil infrastructure monitoring. The core of this transformative shift lies in the integration of artificial intelligence (AI) with sensor technology, focusing on the development of efficient algorithms that drive both device performance enhancements and novel applications in various biomedical and engineering fields. This review delves into the fusion of ML/DL algorithms with sensor technologies, shedding light on their profound impact on sensor design, calibration and compensation, object recognition, and behavior prediction. Through a series of exemplary applications, the review showcases the potential of AI algorithms to significantly upgrade sensor functionalities and widen their application range. Moreover, it addresses the challenges encountered in exploiting these technologies for sensing applications and offers insights into future trends and potential advancements.