Low-cost desktop learning factory to support the teaching of artificial intelligence

IF 2 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

HardwareX Pub Date : 2024-04-19 DOI:10.1016/j.ohx.2024.e00528

Eduardo Orozco , Paulo C. Cárdenas , Jesús A. López , Cinthia K. Rodriguez

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Abstract

The following document details low-cost hardware and open-source available software tools that can be combined to support active teaching methodologies like Problem-Based Learning (PBL) and incorporate work-oriented technological skills in students. This proposal presents a prototype of Open Educational Resources (OER) that integrates software and hardware tools for the specific purpose of facilitating instruction in Artificial Intelligence. The hardware consists of affordable electronic devices, including an Arduino board, servo motors, sensors, a relay and a motor, all integrated into a scaled conveyor belt. On the other hand, open software was used to implement an image classification program with different features (shape, color, size, among others). The exact construction steps, circuits, and code are presented in detail and should encourage other scientists to replicate the experimental setup, especially if they are looking for experimental teaching of artificial intelligence, since the system allows object classification using the machine learning paradigm to facilitate the teaching of artificial intelligence concepts with computer vision concepts.

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支持人工智能教学的低成本桌面学习工厂

以下文件详细介绍了低成本硬件和开源软件工具，它们可以结合起来支持主动教学法，如基于问题的学习（PBL），并将以工作为导向的技术技能融入学生的学习中。本提案介绍了一个开放式教育资源（OER）原型，它整合了软件和硬件工具，专门用于促进人工智能教学。硬件由价格低廉的电子设备组成，包括 Arduino 板、伺服电机、传感器、继电器和电机，所有这些都集成在一个按比例缩放的传送带上。另一方面，开放式软件被用来实现一个具有不同特征（形状、颜色、大小等）的图像分类程序。我们详细介绍了具体的构造步骤、电路和代码，这应该会鼓励其他科学家复制实验装置，特别是如果他们正在寻找人工智能的实验教学，因为该系统可以利用机器学习范式进行物体分类，从而促进人工智能概念与计算机视觉概念的教学。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

HardwareX Engineering-Industrial and Manufacturing Engineering

CiteScore

4.10

自引率

18.20%

发文量

124

审稿时长

24 weeks

期刊介绍： HardwareX is an open access journal established to promote free and open source designing, building and customizing of scientific infrastructure (hardware). HardwareX aims to recognize researchers for the time and effort in developing scientific infrastructure while providing end-users with sufficient information to replicate and validate the advances presented. HardwareX is open to input from all scientific, technological and medical disciplines. Scientific infrastructure will be interpreted in the broadest sense. Including hardware modifications to existing infrastructure, sensors and tools that perform measurements and other functions outside of the traditional lab setting (such as wearables, air/water quality sensors, and low cost alternatives to existing tools), and the creation of wholly new tools for either standard or novel laboratory tasks. Authors are encouraged to submit hardware developments that address all aspects of science, not only the final measurement, for example, enhancements in sample preparation and handling, user safety, and quality control. The use of distributed digital manufacturing strategies (e.g. 3-D printing) is encouraged. All designs must be submitted under an open hardware license.