Design of Embedded Artifical Intelligence Experiment Platform Based on Python
To address the growing demand for artificial intelligence (AI) talent in higher education and enhance students' ability to apply interdisciplinary knowledge, this paper presents the design of an embedded AI experimental platform based on Python. The platform utilizes image recognition as a case study to carry out machine learning and deep learning experiments, so that students could gain a comprehensive understanding of AI algorithm development on embedded systems. The platform uses OrangePi as the embedded terminal, deploys OpenCV for image processing, and integrates scikit-learn for machine learning algorithms and Tencent nonn for deep learning algorithms. By providing hands-on experimentation opportunities, the platform aims to foster students' independent learning, stimulate their interest in scientific research, and enhance their innovation capabilities.
Authors
- Chunfei Zhang (ORCID: https://orcid.org/0000-0003-3657-3487)
- Pengfei Liu (ORCID: https://orcid.org/0000-0001-7122-9126)
- Nan Liang (ORCID: https://orcid.org/0000-0002-7733-862X)
- Yu Zhang (ORCID: https://orcid.org/0000-0001-8296-154X)
Institutions
- Jilin International Studies University (CN)
- Changchun University (CN)
Publication Details
- Published
- 2025-04-18
- DOI
- https://doi.org/10.1109/icccs65393.2025.11069605
- Primary Topic
- Robotics and Automated Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00