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.

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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
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article

Design of Embedded Artifical Intelligence Experiment Platform Based on Python

Chunfei Zhang, Pengfei Liu, Nan Liang, Yu Zhang
Robotics and Automated Systems
article

Design of Embedded Artifical Intelligence Experiment Platform Based on Python

Chunfei Zhang, Pengfei Liu, Nan Liang, Yu Zhang
article en

Abstract

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.

Jilin International Studies University (CN), Changchun University (CN)
Openalex Percentile: Top 80%
Robotics and Automated Systems
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