Review Article
Tiny Machine Learning for Resource-Constrained Microcontrollers
Table 3
Summary of emerging techniques of TinyML.
| Technique | Main features |
| Federated learning | Edge devices collaboratively train an ML model | Improved data privacy and security | E.g., TinyFedTL [89], centralized, and decentralized approaches |
| Transfer learning | Uses older ML models to generate a new one | E.g., TinyTL [91] |
| On-device learning | Uses streaming data for training ML models in a microcontroller | E.g., TinyOL [22] and NanoEdge AI Studio[7] |
| LPWAN | Long-range, low power, and low data rate | E.g., LoRaWAN, Sigfox, NB-IoT, and LTE-M |
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