| Summary: | 碩士 === 國立中央大學 === 資訊工程學系在職專班 === 107 === At present, mainstream AI technology mostly relies on high-performance computer hosts, and embedded systems running on microcontrollers are rare. If the mature AI technology can be run on the microcontroller, you can not only let AI technology be applied in more fields, but also bring considerable power saving in many applications. In this research, the virtual machine was added to enable the microcontroller to be flexibly deployed, so that the deep neural network application implemented in the microcontroller can be deployed in a more convenient manner. After making up for the gap in the convenience of the deep neural network between the microcontroller and the host computer, the aforementioned goals will become feasible. The subsequent experiments also verified the function of the virtual machine and the correctness of the implemented neural network. This research preserves the advantages of the microcontroller and overcomes its shortcomings while bringing deep neural network applications into the microcontroller-based embedded system. Compared with high-energy and high-cost hosts, the extremely low power consumption system of this research will bring considerable energy savings.
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