Integration of Digital Twin, IoT and LoRa in SCARA Robots for Decentralized Automation with Wireless Sensor Networks DOI Creative Commons
William Aparecido Celestino Lopes,

Adilson Cunha Rusteiko,

Cleiton Rodrigues Mendes

et al.

Eng—Advances in Engineering, Journal Year: 2025, Volume and Issue: 6(5), P. 90 - 90

Published: April 26, 2025

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

Language: Английский

Digital twin (DT) and extended reality (XR) for building energy management DOI

Seungkeun Yeom,

Juui Kim,

Hyuna Kang

et al.

Energy and Buildings, Journal Year: 2024, Volume and Issue: 323, P. 114746 - 114746

Published: Aug. 31, 2024

Language: Английский

Citations

9
Harnessing digital twins and industrial-IoT for cutting-edge mining automation: A methodological and technology assessment prototype DOI

Sreekant Sreedharan,

Muthu Ramachandran,

Dharavath Ramesh

et al.

Computers & Industrial Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 110871 - 110871

Published: Jan. 1, 2025

Language: Английский

Citations

1
Load balancing routing algorithm of industrial wireless network for digital twin DOI

Linjie Xiao,

Shining Li, Qin Wen

et al.

Computer Networks, Journal Year: 2025, Volume and Issue: unknown, P. 111059 - 111059

Published: Jan. 1, 2025

Language: Английский

Citations

1
IoT‐5G and B5G/6G resource allocation and network slicing orchestration using learning algorithms DOI Creative Commons
Ado Adamou Abba Ari,

Faustin Samafou,

Arouna Ndam Njoya

et al.

IET Networks, Journal Year: 2025, Volume and Issue: 14(1)

Published: Jan. 1, 2025

Abstract The advent of 5G networks has precipitated an unparalleled surge in demand for mobile communication services, propelled by the sophisticated wireless technologies. An increasing number countries are moving from fourth generation (4G) to fifth (5G) networks, creating a new expectation services that dynamic, transparent, and differentiated. It is anticipated these will be adapted multitude use cases become standard practice. diversity increasingly complex network infrastructures present significant challenges, particularly management resources orchestration services. Network Slicing emerging as promising approach address it facilitates efficient Resource Allocation (RA) supports self‐service capabilities. However, effective segmentation implementation requires development robust algorithms guarantee optimal RA. In this regard, artificial intelligence machine learning (ML) have demonstrated their utility analysis large datasets facilitation intelligent decision‐making processes. certain ML methodologies limited ability adapt evolving environments characteristic beyond (B5G/6G). This paper examines specific challenges associated with evolution B5G/6G particular focus on solutions RA dynamic slicing requirements. Moreover, article presents potential avenues further research domain objective enhancing efficiency next‐generation through adoption innovative technological solutions.

Language: Английский

Citations

1
Modeling indoor thermal comfort in buildings using digital twin and machine learning DOI Creative Commons

Ziad ElArwady,

A. A. Kandil,

Mohanad Afiffy

et al.

Developments in the Built Environment, Journal Year: 2024, Volume and Issue: 19, P. 100480 - 100480

Published: June 5, 2024

Digital Twin (DT) concept is used in different domains and industries, including the building industry, as it has physical digital assets with help of Building Information Modeling (BIM). Technologies methodologies constantly enrich industry because amount data generated during stages considerable a tremendous effect on lifecycle building. Previous research underscores importance seamlessly exchanging information between within comprehensive framework, particularly emphasizing integration BIM various systems to enhance efficiency prevent loss. Despite advancements technologies, challenges persist optimizing methods for integrating into DT frameworks, ensuring interoperability, scalability, real-time monitor control. This study addresses this gap by proposing platform that integrates IoT technologies. The developed five main stages: 1) acquiring electronic from laser scanner, 2) developing Wi-Fi module replica, 3) constructing elements platform, 4) performing analysis 5) implementing thermal comfort prediction models. Two machine learning models (Facebook prophet, NeuralProphet) are implemented predict comfort. best predictive model identified evaluating its error function using historical training collected facility operation. A case demonstrates practical application proposed framework. involves real where control indoor environments. By utilizing predefined models, ensures accuracy, consistency, usability. outputs reveal Neuralprophet provides good results.

Language: Английский

Citations

8
Unlocking a Promising Future: Integrating Blockchain Technology and FL-IoT in the Journey to 6G DOI Creative Commons
Fatemah Alghamedy, Nahla El-Haggar, Albandari Alsumayt

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 115411 - 115447

Published: Jan. 1, 2024

The rapid advancement of technology has set higher standards for the next generation wireless communication networks, known as 6G. These networks go beyond simple task connecting devices and aim to establish a self-sustaining system within society. One key factors in achieving this goal is integration AI services apps through Internet Things (IoT), which will be made possible with support 6G technology. artificial intelligence (AI) play crucial role enhancing protocols, architectures, operations networks. To achieve collaborative IoT applications, Federated Learning (FL) emerged popular method. FL enables training without need data sharing, ensuring privacy security. However, also faces challenges, such presence malicious risk single-point failure. address these concerns, blockchain (BCT) offers secure efficient solution. By leveraging blockchain, issues can effectively tackled, providing reliable framework implementing FL-IoT applications.

Language: Английский

Citations

7
Model-based prototype design, construction and operation of closed-loop control system of solid waste treatment unit DOI
Dawei Hu, Shuaishuai Li, Xiaolei Liu

et al.

Acta Astronautica, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Deep learning technology: enabling safe communication via the internet of things DOI Creative Commons
Ramiz Salama, Hitesh Mohapatra,

Tuğşad Tülbentçi

et al.

Frontiers in Communications and Networks, Journal Year: 2025, Volume and Issue: 6

Published: Feb. 4, 2025

Introduction The Internet of Things (IoT) is a new technology that connects billions devices. Despite offering many advantages, the diversified architecture and wide connectivity IoT make it vulnerable to various cyberattacks, potentially leading data breaches financial loss. Preventing such attacks on ecosystem essential ensuring its security. Methods This paper introduces software-defined network (SDN)-enabled solution for vulnerability discovery in systems, leveraging deep learning. Specifically, Cuda-deep neural (Cu-DNN), Cuda-bidirectional long short-term memory (Cu-BLSTM), Cuda-gated recurrent unit (Cu-DNNGRU) classifiers are utilized effective threat detection. approach includes 10-fold cross-validation process ensure impartiality findings. most recent publicly available CICIDS2021 dataset was used train hybrid model. Results proposed method achieves an impressive recall rate 99.96% accuracy 99.87%, demonstrating effectiveness. model also compared benchmark classifiers, including Cuda-Deep Neural Network, Cuda-Gated Recurrent Unit, (Cu-DNNLSTM Cu-GRULSTM). Discussion Our technique outperforms existing based evaluation criteria as F1-score, speed efficiency, accuracy, precision. shows strength detection highlights potential combining SDN with learning assessment.

Language: Английский

Citations

0
A Comprehensive Review and Exploration of Digital Twin Technology to Map the Future of Personalized Healthcare DOI

M. Suresh,

A. Punitha,

A. Anbarasi

et al.

Advances in healthcare information systems and administration book series, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 28

Published: Feb. 4, 2025

Digital Twin (DT) as a virtual version of product becoming more and popular across many industries especially in the area medical care. To generate testable simulated electronic structure, massive amounts information must be collected through Internet Things (IoT) to support related application. This technology assists alerting person receiving care events such medication refills, modifications diet, doctor visits, life regular food patterns, blood glucose readings. DT makes use prototypes driven by Artificial Intelligence (AI) significant amount gathered from various IoT devices. Using intimate lens look at state customized healthcare now its plans for future. Through case studies examples, demonstrate transformative potential enhancing patient outcomes, optimizing delivery, advancing personalized medicine. Furthermore, within larger framework sector Fourth Industrial Revolution.

Language: Английский

Citations

0
Barriers and Challenges for Digital Twin Adoption in Healthcare Supply Chain and Operations Management DOI
Anil Kumar Sharma, Manoj Kumar Srivastava, Ritu Sharma

et al.

Global Business Review, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 6, 2025

The healthcare sector has undergone significant changes in recent times due to the implementation of digitalization and Industry 4.0 technology. Digital Twins (DTs), which are virtual replicas physical objects, products and/or services, have potential become a competitive advantage within industry. Our present study aims fill existing research gap contribute advancement DT supply chain operations management by finding barriers for adoption. We achieved this synthesizing relevant literature conducting systematic review. further categorized using Technology-Organization-Environment (TOE) framework as outcome research, both theoretical contribution assist industry practitioners focusing on specific their domain successful future avenues proposed based identified barriers.

Language: Английский

Citations

0