Augmented reality monitoring system for cross-belt conveyor in advanced automation line / Sukarnur Che Abdullah ... [et al.]
Remote monitoring systems are increasingly adopted as one of the control strategies in contemporary industrial operations. However, the integration of Augmented Reality (AR) within industrial applications remains limited due to a deficit in comprehensive research. In alignment with Industry 4.0 prin...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
UiTM Press
2025
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/116641/1/116641.pdf https://ir.uitm.edu.my/id/eprint/116641/ https://jmeche.uitm.edu.my/ |
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| Summary: | Remote monitoring systems are increasingly adopted as one of the control strategies in contemporary industrial operations. However, the integration of Augmented Reality (AR) within industrial applications remains limited due to a deficit in comprehensive research. In alignment with Industry 4.0 principles, the deployment of AR in automation introduces a spectrum of possibilities for manufacturing sectors, particularly in critical production processes like material handling. This motivates our initiative to develop a simulation of a cross-belt conveyor system. The algorithms for the conveyor system were implemented using C# within Visual Studio and Unity environments. The algorithm's efficacy was validated through its application to a basic material handling process, specifically a barcode sorting conveyor. This project was realized by embedding AR monitoring capabilities within the conveyor system, facilitating real-time simulation synchronisation between a virtual conveyor model and its counterpart. Data transmission was orchestrated via a Python script, sensor_app.py’ which communicated the data to a dedicated web interface. An Android application, “AR Simulation” was developed to deliver AR-based simulation and visualization. Within the application interface, the quantities of items sorted into respective containers were displayed dynamically. The monitoring algorithm’s functionality was verified by deploying the AR Simulation app and evaluating its performance. Moreover, the system periodically logs data into a CSV file for archival and analytical purposes. The proposed system is also designed to support a web-based interface, enabling remote access to the data across multiple devices via wireless networks. The findings indicate that the AR Simulation application is a robust tool, with AR’s interactive features effectively rendering data under the defined algorithms. This research enhances the current understanding of AR technology’s role in industrial applications, specifically in the context of remote monitoring within manufacturing environments. |
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