Blockchain Empowered Federated Learning with Edge Computing for Digital Twin Systems in Urban Air Mobility

Nguyen, Tuan Anh; Kaliappan, Vishnu Kumar; Jeon, Seong Gyu; Jeon, Kwon-su; Lee, Jae Woo; Dai, Min

doi:10.1007/978-981-19-2635-8_69

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…This technology finds extensive applications in storage and inventory management, supply chain monitoring, access control, aviation transportation, agriculture, healthcare, and more, improving efficiency and automation in various fields [ 39 ]. Wireless Networks, in particular, suggest an immense role in sending data from a source to a connected gateway, a role supported by a variety of wireless network technologies such as WPAN, WLAN, WWAN, and LPWAN that are addressed in [ 18 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 ]. The existing commercial 4G or 5G LTE communication networks, utilizing the transmission of data packets through the well-established Internet Protocol (IP), serves as a base to sustain the architecture of wireless communication networks in general.…”

Section: Reviewing Relevant Technologies and Dt Componentsmentioning

confidence: 99%

“…Particularly in the context of establishing connectivity among IoT devices like sensors, the primary role is the selection of a network with wide coverage and low power consumption. The LoRa network meets these needs, is open, and is used in articles [ 25 , 39 , 40 , 41 , 42 , 44 ]. In cases where the application requires a higher data rate, Bluetooth technology can be used, as mentioned in the article [ 44 ], but it has significantly higher power consumption compared to LoRa, and the coverage is 100 m for Bluetooth 4.x and 200 m for Bluetooth 5.x.…”

Section: Reviewing Relevant Technologies and Dt Componentsmentioning

confidence: 99%

“…The LoRa network meets these needs, is open, and is used in articles [ 25 , 39 , 40 , 41 , 42 , 44 ]. In cases where the application requires a higher data rate, Bluetooth technology can be used, as mentioned in the article [ 44 ], but it has significantly higher power consumption compared to LoRa, and the coverage is 100 m for Bluetooth 4.x and 200 m for Bluetooth 5.x. For applications aimed at object identification and detection, such as products in warehouses and animals in agricultural operations, RFID technology is a suitable choice as mentioned in articles [ 43 , 45 ].…”

Section: Reviewing Relevant Technologies and Dt Componentsmentioning

confidence: 99%

“…In recent times, Distributed Ledger Technologies (DLT), such as blockchain [ 44 , 53 ], have emerged to add to user authentication and data integrity regarding data sharing. To unlock its full potential and achieve its envisioned advantages, addressing outstanding concerns surrounding the technology is imperative.…”

Section: Reviewing Relevant Technologies and Dt Componentsmentioning

confidence: 99%

See 3 more Smart Citations

Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review

Peladarinos

Piromalis

Cheimaras

et al. 2023

Sensors

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Digital Twins serve as virtual counterparts, replicating the characteristics and functionalities of tangible objects, processes, or systems within the digital space, leveraging their capability to simulate and forecast real-world behavior. They have found valuable applications in smart farming, facilitating a comprehensive virtual replica of a farm that encompasses vital aspects such as crop cultivation, soil composition, and prevailing weather conditions. By amalgamating data from diverse sources, including soil, plants condition, environmental sensor networks, meteorological predictions, and high-resolution UAV and Satellite imagery, farmers gain access to dynamic and up-to-date visualization of their agricultural domains empowering them to make well-informed and timely choices concerning critical aspects like efficient irrigation plans, optimal fertilization methods, and effective pest management strategies, enhancing overall farm productivity and sustainability. This research paper aims to present a comprehensive overview of the contemporary state of research on digital twins in smart farming, including crop modelling, precision agriculture, and associated technologies, while exploring their potential applications and their impact on agricultural practices, addressing the challenges and limitations such as data privacy concerns, the need for high-quality data for accurate simulations and predictions, and the complexity of integrating multiple data sources. Lastly, the paper explores the prospects of digital twins in agriculture, highlighting potential avenues for future research and advancement in this domain.

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Section: Reviewing Relevant Technologies and Dt Componentsmentioning

confidence: 99%

Section: Reviewing Relevant Technologies and Dt Componentsmentioning

confidence: 99%

Section: Reviewing Relevant Technologies and Dt Componentsmentioning

confidence: 99%

Section: Reviewing Relevant Technologies and Dt Componentsmentioning

confidence: 99%

See 2 more Smart Citations

Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review

Peladarinos

Piromalis

Cheimaras

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…In this application, the EHK method was employed to develop aerodynamic models of six aerodynamic coefficients for an eVTOL-KP2 aircraft [50,51], including: drag coefficient (C D ), lift coefficient (C L ), pitching moment coefficient (C m ), side force coefficient (C Y ), rolling moment coefficient (C l ), and yawing moment coefficient (C n ). The tridimensional depiction of the KP-2 design is illustrated in Figure 9, accompanied by a comprehensive overview of its design characteristics provided in Table 9.…”

Section: Generation Of Aerodynamic Models For An Evtol Vehicle For Ur...mentioning

confidence: 99%

Extended Hierarchical Kriging Method for Aerodynamic Model Generation Incorporating Multiple Low-Fidelity Datasets

Pham,

Tyan,

Nguyen

et al. 2023

Aerospace

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Multi-fidelity surrogate modeling (MFSM) methods are gaining recognition for their effectiveness in addressing simulation-based design challenges. Prior approaches have typically relied on recursive techniques, combining a limited number of high-fidelity (HF) samples with multiple low-fidelity (LF) datasets structured in hierarchical levels to generate a precise HF approximation model. However, challenges arise when dealing with non-level LF datasets, where the fidelity levels of LF models are indistinguishable across the design space. In such cases, conventional methods employing recursive frameworks may lead to inefficient LF dataset utilization and substantial computational costs. To address these challenges, this work proposes the extended hierarchical Kriging (EHK) method, designed to simultaneously incorporate multiple non-level LF datasets for improved HF model construction, regardless of minor differences in fidelity levels. This method leverages a unique Bayesian-based MFSM framework, simultaneously combining non-level LF models using scaling factors to construct a global trend model. During model processing, unknown scaling factors are implicitly estimated through hyperparameter optimization, resulting in minimal computational costs during model processing, regardless of the number of LF datasets integrated, while maintaining the necessary accuracy in the resulting HF model. The advantages of the proposed EHK method are validated against state-of-the-art MFSM methods through various analytical examples and an engineering case study involving the construction of an aerodynamic database for the KP-2 eVTOL aircraft under various flying conditions. The results demonstrated the superiority of the proposed method in terms of computational cost and accuracy when generating aerodynamic models from the given multi-fidelity datasets.

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Real-Time Reliability Monitoring on Edge Computing: a Systematic Mapping

Diván,

Shchemelinin,

Carranza

et al. 2023

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Scenario: System reliability monitoring focuses on determining the level at which the system works as expected (under certain conditions and over time) based on requirements. The edge computing environment is heterogeneous and distributed. It may lack central control due to the scope, number, and volume of stakeholders. Objective: To identify and characterize the Real-time System Reliability Monitoring strategies that have considered Artificial Intelligence models for supporting decision-making processes. Methodology: An analysis based on the Systematic Mapping Study was performed on December 14, 2022. The IEEE and Scopus databases were considered in the exploration. Results: 50 articles addressing the subject between 2013 and 2022 with growing interest. The core use of this technology is related to networking and health areas, articulating Body sensor networks or data policies management (collecting, routing, transmission, and workload management) with edge computing. Conclusions: Real-time Reliability Monitoring in edge computing is ongoing and still nascent. It lacks standards but has taken importance and interest in the last two years. Most articles focused on Push-based data collection methods for supporting centralized decision-making strategies. Additionally, to networking and health, it concentrated and deployed on industrial and environmental monitoring. However, there are multiple opportunities and paths to walk to improve it. E.g., data interoperability, federated and collaborative decision-making models, formalization of the experimental design for measurement process, data sovereignty, organizational memory to capitalize previous knowledge (and experiences), calibration and recalibration strategies for data sources.

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Blockchain Empowered Federated Learning with Edge Computing for Digital Twin Systems in Urban Air Mobility

Cited by 4 publications

References 17 publications

Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review

Enhancing Smart Agriculture by Implementing Digital Twins: A Comprehensive Review

Extended Hierarchical Kriging Method for Aerodynamic Model Generation Incorporating Multiple Low-Fidelity Datasets

Real-Time Reliability Monitoring on Edge Computing: a Systematic Mapping

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