Evaluation of 5G-capable framework for highly mobile, scalable human-machine interfaces in cyber-physical production systems

Mertes, Jan; Lindenschmitt, Daniel; Amirrezai, Masoud; Tashakor, Nima; Glatt, Moritz; Schellenberger, Christian; Shah, Swati Matwankar; Karnoub, Ali; Hobelsberger, Christopher; Yi, Li; Götz, Stefan; Aurich, Jan C.; Schotten, Hans D.

doi:10.1016/j.jmsy.2022.08.009

Cited by 21 publications

(10 citation statements)

References 42 publications

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“…Research in this area is focused not only on enhancing the technological capabilities of these systems but also on improving user engagement and overall health outcomes. The combination of AI, advanced sensor technology, and userfriendly interfaces is expected to lead to a new generation of fitness monitoring systems that are more accurate, engaging, and effective in promoting physical well-being [36]. As these technologies continue to evolve, they offer exciting possibilities for the future of personal fitness and wellness.…”

Section: H Future Directions and Emerging Technologiesmentioning

confidence: 99%

“…Top-down approaches initiate with a human detector and proceed to analyze body joints within predetermined boundary boxes. Notable examples of top-down methods include PoseNet [36], HourglassNet [37], and Hornet [38]. Alternatively, bottom-up methods, such as Open space [39] and PifPaf [40], offer a different approach to body localization, each with their unique methodologies and applications.…”

Section: A Proposed Approachmentioning

confidence: 99%

See 1 more Smart Citation

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Tileubay,

Yerekeshova,

Baiganova

et al. 2024

IJACSA

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The fusion of augmented reality (AR) and deep learning technologies has ushered in a transformative era in the realm of real-time physical activity monitoring. This research paper introduces a system that harnesses the capabilities of PoseNet-based skeletal keypoint extraction and deep neural networks to achieve unparalleled accuracy and real-time functionality in the identification and classification of a wide spectrum of physical activities. With an impressive accuracy rate of 98% within 100 training epochs, the system proves its mettle in precise activity recognition, making it invaluable in domains such as fitness training, physical education, sports coaching, and home-based fitness. The system's real-time feedback mechanism, bolstered by AR technology, not only enhances user engagement but also motivates users to optimize their exercise routines. This paper not only elucidates the system's architecture and functionality but also highlights its potential applications across diverse fields. Furthermore, it delineates the trajectory of future research avenues, including the development of advanced feedback mechanisms, exploration of multi-modal sensing techniques, personalization for users, assessment of long-term impacts, and endeavors to ensure accessibility, inclusivity, and data privacy. In essence, this research sets the stage for the evolution of real-time physical activity monitoring, offering a compelling framework to improve fitness, physical education, and athletic training while promoting healthier lifestyles and the overall well-being of individuals worldwide.

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Section: H Future Directions and Emerging Technologiesmentioning

confidence: 99%

Section: A Proposed Approachmentioning

confidence: 99%

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Tileubay,

Yerekeshova,

Baiganova

et al. 2024

IJACSA

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“…5G is designed to enhance the primary capabilities of a mobile network's core. Utilising network slicing and private networks, 5G technology may accommodate the needs of current HMIs in production systems and enables HMI's essential mobility and scalability for interacting with many machines via a single input interface [58]. Additionally, since different machines and equipment involved in monitoring services could generate different data streams, 5G leverage distinct network slices to satisfy different devices' requirements.…”

Section: G In Cyber-physical Systems Related Servicesmentioning

confidence: 99%

“…Expected impacts of introducing CPS in the service field also concern service technicians, who can exploit more powerful mobile work support systems, such as wearable devices, providing vital information that may improve service efficiency. In any case, since the involvement of humans has high relevance in the provision of CPS‐based services, the development of mobile HMI (HMIs) could often be critical due to the necessity to develop customer‐specific interfaces and due to the wireless implementation of such HMI in reconfigurable and adaptable cyber‐physical production systems [58].…”

Section: G Supporting Digital Servitizationmentioning

confidence: 99%

5G supporting digital servitization in manufacturing: An exploratory survey

Cimini,

Lagorio,

Pinto

et al. 2023

IET Collab Intel Manufact

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Digital servitization is a business model transformation process enabled by the use of digital technologies to create or improve industrial services and product‐service offerings by creating value and competitive advantage increasing customer satisfaction and loyalty as well as company revenue streams. 5G networks can enable digital servitization of manufacturing by providing faster, more secure, and more reliable communications between machines, devices, and humans. This paper explores the impact of adopting 5G technologies on servitization and identifies the services that can benefit most from 5G networks. The research consists of two parts: a literature review of the technologies currently used in the design and provision of industrial services that could benefit from 5G networks and an exploratory survey involving manufacturing companies that have started the digital servitization journey. The main results emerging from the research suggest that 5G can profoundly impact services supported by Augmented Reality, Cloud computing, and Cyber‐physical systems, mainly concerning maintenance, workforce training, machine diagnosis and monitoring.

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“…To address these deficiencies, the HMI-BC training kit capitalizes on advanced HMI technology, enabling students to directly interact with automated systems and assess their control capabilities in a real-world environment [10], [11]. Within the context of rapid industrial development, particularly in the era of the IoT, this approach facilitates a deeper comprehension of utilizing HMI technology to control increasingly interconnected automated systems [11], [12]. Thus, this research assumes a pivotal role in shaping the latest teaching and learning approaches for automation control while making a substantial contribution to the development of a relevant IEE curriculum that aligns with ever-evolving industrial needs.…”

Section: Introductionmentioning

confidence: 99%

Human Machine Interface-Based Control Training Kit as Innovative Learning Media to Enhance Students’ Automation Control Skills in the Industry 4.0 Era

Aswardi,

Putra Yanto,

Dewi

et al. 2023

TEM Journal

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This research investigates the effectiveness of the Human-Machine Interface-based control (HMI-BC) training kit as an innovative learning media in enhancing the Automation Control Skills (ACSs) of Industrial Electrical Engineering (IEE) students in the Industry 4.0 Era. The study focuses on evaluating the students' ACSs in the Electrical Machine Control Course (EMCC) after using the HMI-BC training kit as a practical learning media. The research adopts a quasi-experimental design with a One-Group Pre-test and Post-test design. The student’s ACSs data is collected using a performance assessment instrument. The impact of the HMI-BC training kit in enhancing ACSs was evaluated based on the differential analysis of pre-test and post-test scores using the paired-sample t-test. Furthermore, the effect size of the HMI-BC training kit on the learning process was determined using Cohen's d effect size analysis. The results reveal a significant improvement in the students' ACSs as evaluated through the assessment of the performance indicators. Based on the evaluation, the findings demonstrate a notable enhancement in students' ACSs. The HMI-BC Training Kit, developed to align with the characteristics of the learning material and industrial advancements, proves to be effective in enhancing students' ACSs, aligning with the evolving needs of the industry. These findings highlight the importance of incorporating the HMI-BC Training Kit in the learning process of motor control to equip students with relevant automation control competencies, ultimately preparing them for the industrial demands of the future.

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Evaluation of 5G-capable framework for highly mobile, scalable human-machine interfaces in cyber-physical production systems

Cited by 21 publications

References 42 publications

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

Development of Deep Learning Enabled Augmented Reality Framework for Monitoring the Physical Quality Training of Future Trainers-Teachers

5G supporting digital servitization in manufacturing: An exploratory survey

Human Machine Interface-Based Control Training Kit as Innovative Learning Media to Enhance Students’ Automation Control Skills in the Industry 4.0 Era

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