Integration of Digital Twin, IoT and LoRa in SCARA Robots for Decentralized Automation with Wireless Sensor Networks

The integration of Digital Twin (DT), Internet of Things (IoT), and Long Range Wireless (LoRa) technology in industrial automation increases efficiency, flexibility, and real-time monitoring. This study proposes a decentralized automation architecture for SCARA robots, leveraging wireless sensor networks to improve scalability, reduce the number of infrastructure components, and optimizing data-driven decision-making. Experimental validation demonstrated a 74.9% reduction in cycle time, decreasing from 55.42 s to 13.91 s across all test scenarios. The system achieved a 98.6% packet delivery success rate, ensuring reliable communication, while latency remained between 1 and 2 s, maintaining synchronization between the real robot and its digital twin. The main contributions include the following: (i) a decentralized control framework for SCARA robots, (ii) an evaluation of LoRa-based wireless communication, and (iii) experimental validation of feasibility. The results confirm the effectiveness of the system in stable real-time data transmission and precise robotic movements, offering a cost-effective alternative to conventional structures. Despite the advantages, challenges such as data security, interoperability, and real-time synchronization require further research. This study provides insights into the practical implementation of DT, IoT, and LoRa in industrial robotics, paving the way for advancements in smart manufacturing and Industry 4.0.

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Publication Details

Journal
Eng—Advances in Engineering
Published
2025-04-26
DOI
https://doi.org/10.3390/eng6050090
Citations
3
Primary Topic
IoT Networks and Protocols
Type
article
Field-Weighted Citation Impact
2.19

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article

Integration of Digital Twin, IoT and LoRa in SCARA Robots for Decentralized Automation with Wireless Sensor Networks

Cleiton Rodrigues Mendes, William Aparecido Celestino Lopes, Marcelo Tsuguio Okano, Adilson Cunha Rusteiko et al.
3 citations
Eng—Advances in Engineering
IoT Networks and Protocols
2.19
article

Integration of Digital Twin, IoT and LoRa in SCARA Robots for Decentralized Automation with Wireless Sensor Networks

Cleiton Rodrigues Mendes, William Aparecido Celestino Lopes, Marcelo Tsuguio Okano, Adilson Cunha Rusteiko, Nicolas Vinicius Cruz Honório
article en
3 citations

Abstract

The integration of Digital Twin (DT), Internet of Things (IoT), and Long Range Wireless (LoRa) technology in industrial automation increases efficiency, flexibility, and real-time monitoring. This study proposes a decentralized automation architecture for SCARA robots, leveraging wireless sensor networks to improve scalability, reduce the number of infrastructure components, and optimizing data-driven decision-making. Experimental validation demonstrated a 74.9% reduction in cycle time, decreasing from 55.42 s to 13.91 s across all test scenarios. The system achieved a 98.6% packet delivery success rate, ensuring reliable communication, while latency remained between 1 and 2 s, maintaining synchronization between the real robot and its digital twin. The main contributions include the following: (i) a decentralized control framework for SCARA robots, (ii) an evaluation of LoRa-based wireless communication, and (iii) experimental validation of feasibility. The results confirm the effectiveness of the system in stable real-time data transmission and precise robotic movements, offering a cost-effective alternative to conventional structures. Despite the advantages, challenges such as data security, interoperability, and real-time synchronization require further research. This study provides insights into the practical implementation of DT, IoT, and LoRa in industrial robotics, paving the way for advancements in smart manufacturing and Industry 4.0.

Eng—Advances in EngineeringVol. 6(5)
Serviço Nacional de Aprendizagem Industrial (BR), Universidade Paulista (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Openalex Percentile: Top 12%
IoT Networks and Protocols
2.19
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