| dc.description.abstract | To facilitate a smart manufacturing environment, considerable on-site production information must be extracted. However, in real factories, many old equipment and devices are not equipped with interfaces to extract and transmit digital data, or have compatibility problems against standardized data extraction and exchange. Therefore, this study designed an embedded instrument identification system to automatically extract digits, pointers, and waveforms on a conventional instrument and digitalize these data to solve the problem of equipment information integration. The virtual instrument system performs corresponding image processing and extracts data on digits, points and waveforms, and recognizes digits by neural network. We used an embedded platform based on ARM Cortex-M7 core with minimized hardware resources. The accuracy rates of the system in identifying digits, pointers, and waveforms reached 76.4%, 73.68%, and 64.7%, respectively. The results verified the feasibility of the proposed embedded virtual instrument system. | en_US |