| 1. |
- Qi, Jun, et al.
(författare)
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IoTBDH-2023: The 5th International Workshop on Internet of Things of Big Data for Healthcare
- 2023
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Ingår i: CIKM 2023 - Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. - : Association for Computing Machinery. ; , s. 5285-5288
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Konferensbidrag (refereegranskat)abstract
- Internet of Things (IoT) enabled technology has rapidly and efficiently facilitate healthcare diagnose and treatment with low-cost and lightweight devices. Big data generated from IoT offers valuable and crucial information to guide decision-making, improve patient outcomes, and decrease healthcare costs, etc. The workshop is aiming to provide an opportunity for researchers and practitioners from both academia and industry to present the state-of-the-art research and applications in utilizing IoT and big data technology for healthcare by presenting efficient scientific and engineering solutions, addressing the needs and challenges for integration with new technologies, and providing visions for future research and development.
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| 2. |
- Yang, Wei, et al.
(författare)
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Adaptive optimization federated learning enabled digital twins in industrial IoT
- 2024
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Ingår i: Journal of Industrial Information Integration. - : Elsevier BV. - 2467-964X .- 2452-414X. ; 41
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Tidskriftsartikel (refereegranskat)abstract
- The Industrial Internet of Things (IIoT) plays a pivotal role in steering enterprises towards comprehensive digital transformation and fostering intelligent production, which serves as a critical pillar of Industry 4.0. Digital twin (DT) emerges as a highly promising technology, enabling the digital transformation of the IIoT by seamlessly bridging physical systems with digital spaces. However, the overall service quality of the IIoT is severely impacted by the resource-limited devices and the massive, heterogeneous and sensitive data in the IIoT. As an innovative distributed machine learning paradigm, federated learning (FL) inherently possesses advantages in handling private and heterogeneous data. In this paper, we propose a novel framework integrating F L with D T-enabled e nabled I IoT, termed FDEI, which combines the merits of both to improve service quality while maintaining trustworthiness. To enhance the modeling efficiency, we develop FedOA, an a daptive o ptimization F L method that dynamically adjusts the local update coefficient and model compression rate in resource-limited IIoT scenarios, to construct the FDEI model. Specifically, leveraging the interdependence between the two variables, we conduct a theoretical analysis of the model convergence rate and derive the associated convergence bounds. Building upon the theoretical analysis, we further propose a joint adaptive adjustment strategy by optimizing the two variables across various clients to minimize runtime differences and accelerate the convergence rate. Numerical results demonstrate that our proposed approach achieves an approximate 68% improvement in convergence speed and a reduction of approximately 66% in traffic consumption compared to the benchmarks (e.g., FedAvg, AFL, and CSFL).
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| 3. |
- Bao, Chunxiong, et al.
(författare)
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High Performance and Stable All-Inorganic Metal Halide Perovskite-Based Photodetectors for Optical Communication Applications
- 2018
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Ingår i: Advanced Materials. - : WILEY-V C H VERLAG GMBH. - 0935-9648 .- 1521-4095. ; 30:38
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Tidskriftsartikel (refereegranskat)abstract
- Photodetectors are critical parts of an optical communication system for achieving efficient photoelectronic conversion of signals, and the response speed directly determines the bandwidth of the whole system. Metal halide perovskites, an emerging class of low-cost solution-processed semiconductors, exhibiting strong optical absorption, low trap states, and high carrier mobility, are widely investigated in photodetection applications. Herein, through optimizing the device engineering and film quality, high-performance photodetectors based on all-inorganic cesium lead halide perovskite (CsPbIxBr3-x), which simultaneously possess high sensitivity and fast response, are demonstrated. The optimized devices processed from CsPbIBr2 perovskite show a practically measured detectable limit of about 21.5 pW cm(-2) and a fast response time of 20 ns, which are both among the highest reported device performance of perovskite-based photodetectors. Moreover, the photodetectors exhibit outstanding long-term environmental stability, with negligible degradation of the photoresponse property after 2000 h under ambient conditions. In addition, the resulting perovskite photodetector is successfully integrated into an optical communication system and its applications as an optical signal receiver on transmitting text and audio signals is demonstrated. The results suggest that all-inorganic metal halide perovskite-based photodetectors have great application potential for optical communication.
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| 4. |
- Ding, Yuemin, et al.
(författare)
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Guest Editorial of the Special section on Emerging Technologies and Applications of Consumer Electronics for Healthy and Sustainable Life
- 2024
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Ingår i: IEEE transactions on consumer electronics. - : Institute of Electrical and Electronics Engineers Inc.. - 0098-3063 .- 1558-4127. ; 70:1, s. 2378-2381
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Tidskriftsartikel (refereegranskat)abstract
- Ensuring a healthy and sustainable life and promoting the wellness of human beings at all ages are essential to sustainable development. For this purpose, consumer electronics play important roles, such as body-centric healthcare, health-related ambient monitoring, sustainable health management, etc. Undoubtedly, in modern health and sustainable applications, Consumer Electronics (CE) is at the forefront of bridging physical and digital worlds, offering innovative solutions to improve health outcomes and enhance sustainable practices.
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| 5. |
- Gbouna, Zakka Vincent, et al.
(författare)
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User-Interactive Robot Skin With Large-Area Scalability for Safer and Natural Human-Robot Collaboration in Future Telehealthcare
- 2021
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Ingår i: IEEE journal of biomedical and health informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 2168-2194 .- 2168-2208. ; 25:12, s. 4276-4288
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Tidskriftsartikel (refereegranskat)abstract
- With the fourth revolution of healthcare, i.e., Healthcare 4.0, collaborative robotics is spilling out from traditional manufacturing and will blend into human living or working environments to deliver care services, especially telehealthcare. Because of the frequent and seamless interaction between robots and care recipients, it poses several challenges that require careful consideration: 1) the ability of the human to collaborate with the robots in a natural manner; and 2) the safety of the human collaborating with the robot. In this regard, we have proposed a proximity sensing solution based on the self-capacitive technology to provide an extended sense of touch for collaborative robots, allowing approach and contact measurement to enhance safe and natural human-robot collaboration. The modular design of our solution enables it to scale up to form a large-area sensing system. The sensing solution is proposed to work in two operation modes: the interaction mode and the safety mode. In the interaction mode, utilizing the ability of the sensor to localize the point of action, gesture command is used for robot manipulation. In the safety mode, the sensor enables the robot to actively avoid obstacles.
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| 6. |
- Hu, Dongxiao, et al.
(författare)
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Embodied AI Through Cloud-Fog Computing: A Framework for Everywhere Intelligence
- 2024
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Ingår i: 2024 33rd International Symposium on Industrial Electronics, ISIE 2024 - Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Embodied AI represents a crucial step towards achieving Artificial General Intelligence (AGI). The next paradigm of Embodied AI involves physical embodiment, enhanced perception capabilities, and adaptive automation. This advances the field significantly, paving the way for broader expansion. Despite the significant progress, existing computing frameworks, like local computation or cloud computing, struggle to meet the substantial demands of Embodied AI. The Cloud-Fog Embodied framework, namely based on CFA (cloud-fog automation) offers a promising solution to address these challenges. Our goal is to drive integration across multiple domains, including AI, robotics and industrial production, to tackle multifaceted challenges and seize opportunities to achieve AGI in the future.
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| 7. |
- Lv, Honghao, et al.
(författare)
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Impacts of Wireless on Robot Control : The Network Hardware-in-the-Loop Simulation Framework and Real-Life Comparisons
- 2023
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Ingår i: IEEE Transactions on Industrial Informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 1551-3203 .- 1941-0050. ; 19:9, s. 9255-9265
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Tidskriftsartikel (refereegranskat)abstract
- As many robot applications become more reliant on wireless communications, wireless network latency and reliability have a growing impact on robot control. This article proposes a network hardware-in-the-loop (N-HiL) simulation framework to evaluate the impacts of wireless on robot control more efficiently and accurately, and then improve the design by employing correlation analysis between communication and control performances. The N-HiL method provides communication and robot developers with more trustworthy network conditions, while the huge efforts and costs of building and testing the entire physical robot system in real life are eliminated. These benefits are showcased in two representative latency-sensitive applications: 1) safe multirobot coordination for mobile robots, and 2) human-motion-based teleoperation for manipulators. Moreover, we deliver a preliminary assessment of two new-generation wireless technologies, the Wi-Fi6 and 5G, for those applications, which has demonstrated the effectiveness of the N-HiL method as well as the attractiveness of the wireless technologies.
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| 8. |
- Lv, Honghao, et al.
(författare)
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Towards Intercontinental Teleoperation : A Cloud-Based Framework for Ultra-Remote Human-Robot Dual-Arm Motion Mapping
- 2023
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Ingår i: Intelligent Robotics and Applications. - : Springer Nature. ; , s. 132-144
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Konferensbidrag (refereegranskat)abstract
- Teleoperated robots offer a unique combination of robotic strength and precision, coupled with human judgment and ingenuity, to enhance productivity and safety in complex, unstructured, and hazardous industrial environments. However, teleoperation over ultra-remote distances has posed a significant challenge, with control performance being compromised by the inherent trade-off between distance and latency. This study presents a novel cloud-based human-robot motion mapping framework for ultra-remote teleoperation. An intuitive dual-arm human-robot motion mapping framework based on capturing human motion has been implemented, and private network connectivity is established using the Google Cloud platform for the efficient transfer of control data required for human-robot motion mapping. Moreover, a novel feedforward control framework is proposed to mitigate the negative impact of high network latency on teleoperation control performance. To demonstrate the feasibility of the proposed approach, an intercontinental teleoperation system between China and Sweden was developed, and a series of practical applications were demonstrated by capturing the motion of an operator in Sweden to control the dual-arm robot located over 7800 km away in China. The proposed feedforward control framework for intercontinental teleoperation has the potential utility for improving human-robot interaction performance in ultra-remote teleoperation scenarios with high network latency. More demonstration videos can be found at https://fsie-robotics.com/intercontinental-teleoperation/.
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| 9. |
- Lyu, Honghao, et al.
(författare)
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GuLiM : A Hybrid Motion Mapping Technique for Teleoperation of Medical Assistive Robot in Combating the COVID-19 Pandemic
- 2022
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Ingår i: IEEE Transactions on Medical Robotics and Bionics. - : Institute of Electrical and Electronics Engineers (IEEE). - 2576-3202. ; 4:1, s. 106-117
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Tidskriftsartikel (refereegranskat)abstract
- Driven by the demand to largely mitigate nosocomial infection problems in combating the coronavirus disease 2019 (COVID-19) pandemic, the trend of developing technologies for teleoperation of medical assistive robots is emerging. However, traditional teleoperation of robots requires professional training and sophisticated manipulation, imposing a burden on healthcare workers, taking a long time to deploy, and conflicting the urgent demand for a timely and effective response to the pandemic. This paper presents a novel motion synchronization method enabled by the hybrid mapping technique of hand gesture and upper-limb motion (GuLiM). It tackles a limitation that the existing motion mapping scheme has to be customized according to the kinematic configuration of operators. The operator awakes the robot from any initial pose state without extra calibration procedure, thereby reducing operational complexity and relieving unnecessary pre-training, making it user-friendly for healthcare workers to master teleoperation skills. Experimenting with robotic grasping tasks verifies the outperformance of the proposed GuLiM method compared with the traditional direct mapping method. Moreover, a field investigation of GuLiM illustrates its potential for the teleoperation of medical assistive robots in the isolation ward as the Second Body of healthcare workers for telehealthcare, avoiding exposure of healthcare workers to the COVID-19.
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| 10. |
- Lyu, Honghao, et al.
(författare)
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Hardware-in-the-Loop Simulation for Evaluating Communication Impacts on the Wireless-Network-Controlled Robots
- 2022
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Ingår i: Proceedings IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society. - : Institute of Electrical and Electronics Engineers (IEEE).
-
Konferensbidrag (refereegranskat)abstract
- More and more robot automation applications have changed to wireless communication, and network performance has a growing impact on robotic systems. This study proposes a hardware-in-the-loop (HiL) simulation methodology for connecting the simulated robot platform to real network devices. This project seeks to provide robotic engineers and researchers with the capability to experiment without heavily modifying the original controller and get more realistic test results that correlate with actual network conditions. We deployed this HiL simulation system in two common cases for wireless-network-controlled robotic applications: (1) safe multi-robot coordination for mobile robots, and (2) human-motion-based teleoperation for manipulators. The HiL simulation system is deployed and tested under various network conditions in all circumstances. The experiment results are analyzed and compared with the previous simulation methods, demonstrating that the proposed HiL simulation methodology can identify a more reliable communication impact on robot systems.
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