Augmented Reality Based Breadboard Circuit Building Guide Application

Thiwanka, Nisal; Chamodika, Umesh; Priyankara, Lahiru; Sumathipala, Sagara; Weerasuriya, G. Thilini

doi:10.1109/icitr.2018.8736156

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…Recently, [9], [10] also present ARbased circuit simulators for educational purpose, but they do not utilize a real breadboard so the learners' transition from virtual to real circuit building would be more difficult. A system similar to ours was recently suggested in [11], which does not demonstrate its feasibility with actual results.…”

Section: Introductionmentioning

confidence: 90%

Augmented Reality Circuit Learning

Wang

Cheung

2021

2021 IEEE International Symposium on Circuits and Systems (ISCAS)

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Building electronic circuits is one of the most common hands-on activities in learning STEM subjects. Beginning students often find it difficult to translate a circuit schematic into the construction of the physical circuit on a breadboard. In this paper, we describe an Augmented Reality circuit learning software that can provide students with step-by-step instructions by placing virtual circuit components on a physical breadboard. We propose a novel image processing pipeline that can robustly identify the planar structure of a breadboard, even in the presence of occluding circuit components on the breadboard. Using a commercially available library of 3D circuit component models, the estimated 3D structure of the breadboard allows us to render arbitrary circuit components on it in real time. Experimental results demonstrate that our algorithms are accurate and can produce realistic-looking virtual circuits.

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Section: Introductionmentioning

confidence: 90%

Augmented Reality Circuit Learning

Wang

Cheung

2021

2021 IEEE International Symposium on Circuits and Systems (ISCAS)

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“…In [10], a guide for creating a breadboard based on augmented reality is implemented. One of the modules in this manual is the Electronic Component Identification Module.…”

Section: Related Workmentioning

confidence: 99%

Preprocessing and improving image quality for identifying elements simple shape in machine vision system to automated industrial machines

Voronin,

Khamidullin,

Semenishchev

et al. 2024

Optics, Photonics, and Digital Technologies for Imaging Applications VIII

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This paper presents an efficient algorithm for finding the location of legs on electronic components. The proposed method has a wide range of applications, including areas such as quality manufacturing, quality control, defect detection, and more.The research described in this article demonstrates the significant potential for automation and optimization in the context of microchip analysis processes. Automated analysis systems can eliminate the need for manual labor, leading to increased efficiency, accuracy, and consistency.

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“…Another AR application was implemented in [80] to detect a breadboard and instruct students on how to build a circuit. The system scanned a circuit diagram for circuit symbols and their connections.…”

Section: Mobilenet-deep Learning Networkmentioning

confidence: 99%

Augmented Reality in Maintenance—History and Perspectives

2023

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Augmented Reality (AR) is a technology that allows virtual elements to be superimposed over images of real contexts, whether these are text elements, graphics, or other types of objects. Smart AR glasses are increasingly optimized, and modern ones have features such as Global Positioning System (GPS), a microphone, and gesture recognition, among others. These devices allow users to have their hands free to perform tasks while they receive instructions in real time through the glasses. This allows maintenance professionals to carry out interventions more efficiently and in a shorter time than would be necessary without the support of this technology. In the present work, a timeline of important achievements is established, including important findings in object recognition, real-time operation. and integration of technologies for shop floor use. Perspectives on future research and related recommendations are proposed as well.

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Augmented Reality Based Breadboard Circuit Building Guide Application

Cited by 5 publications

References 4 publications

Augmented Reality Circuit Learning

Augmented Reality Circuit Learning

Preprocessing and improving image quality for identifying elements simple shape in machine vision system to automated industrial machines

Augmented Reality in Maintenance—History and Perspectives

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