Machine Learning for Microcontroller-Class Hardware - A Review

• Published in: IEEE sensors journal Vol. 22; no. 22; p. 1
• Main Authors: Saha, Swapnil Sayan, Sandha, Sandeep Singh, Srivastava, Mani
• Format: Journal Article
• Language: English
• Published: United States IEEE 15.11.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computational modeling; Data models; Feature projection; Hardware; Internet of Things; Machine learning; Mathematical models; Microcontrollers; model compression; neural architecture search; neural networks; optimization; Random access memory; Sensors; TinyML; Workflow; model compression; sensors; optimization; neural networks; Feature projection; internet-of-things; machine learning; TinyML; neural architecture search; microcontrollers

The advancements in machine learning opened a new opportunity to bring intelligence to the low-end Internet-of-Things nodes such as microcontrollers. Conventional machine learning deployment has high memory and compute footprint hindering their direct deployment on ultra resource-constrained microco...