Aimed at the challenges posed by the increasing penetration of renewable energy sources (RES) in active distribution networks, particularly concerning local consumption and transmission barriers of harvested RES, this...
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Digital Twins and the Internet of things (IoT) are two of the most prominent recent concepts and technologies. the IoT supports many applications that merge the physical withthe cyber world. this highlights the need ...
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ISBN:
(纸本)9781665495127
Digital Twins and the Internet of things (IoT) are two of the most prominent recent concepts and technologies. the IoT supports many applications that merge the physical withthe cyber world. this highlights the need for improved security. Here, we argue that digital twins can help in securing and strengthening the IoT by using them for interacting withthe actual IoT devices. While most digital twins implementations are centralized, we propose to integrate distributed Ledger Technologies (DLTs) and digital twins into the IoT to realize decentralized, secure, available, flexible, and auditable blockchain-based IoT services for IoT devices that follow the W3C Web of things (WoT) standards. In this work, we present the design of SmartTwin, a blockchain-based digital twin framework for which we provide two different implementations using two different blockchains, we present the design trade-offs, and we discuss future research and development directions.
the study proposes an innovative approach to enhance energy efficiency in Wireless sensor Networks (WSNs) for smart city applications. the primary focus is on leveraging distributed artificial intelligence (AI) and mu...
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ISBN:
(纸本)9783031751691;9783031751707
the study proposes an innovative approach to enhance energy efficiency in Wireless sensor Networks (WSNs) for smart city applications. the primary focus is on leveraging distributed artificial intelligence (AI) and multipath routing techniques to address challenges such as unequal clustering, poor cluster head selection, and excessive power consumption within WSNs. the approach uses agent-based clustering, where autonomous AI agents dynamically form clusters of sensor nodes based on real-time data characteristics. these clusters are then used for multipath routing, optimizing energy consumption, reliability, and congestion reduction. the distributed nature of AI agents allows for adaptive cluster formations. this algorithm aims to address issues related to uneven clustering, inefficient cluster head selection, and excessive power consumption. Additionally, the integration of agent-based clustering is proposed, involving the deployment of autonomous AI agents that dynamically cluster sensor nodes based on real-time data properties. these AI agents facilitate self-organization and adaptability, ensuring that clusters accurately reflect the evolving data landscape in urban environments. the approach also employs sophisticated energy management strategies at the sensor node level, such as duty cycling, adaptive transmission power control, and sleep-wake scheduling. Simulations in a smart city environment show significant improvements in energy efficiency, prolonging the network's operational lifespan and improving service quality by mitigating data loss and latency issues. this approach contributes to the sustainable development and performance optimization of smart city infrastructure.
the paper presents an event-triggered distributed model predictive control (DMPC) algorithm for a group of decoupled nonlinear systems under Denial-of-Service (DoS) attacks. By designing the distributed event-triggere...
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ISBN:
(纸本)9781665497701
the paper presents an event-triggered distributed model predictive control (DMPC) algorithm for a group of decoupled nonlinear systems under Denial-of-Service (DoS) attacks. By designing the distributed event-triggered scheme and buffer-based transmission strategy, the resilient control method is formed. the minimum sampling time interval of the closed-loop system is theoretically analyzed. We also develop sufficient conditions to guarantee the recursive feasibility of the algorithm. Simulation results demonstrate the effectiveness of the proposed distributed MPC control scheme.
Photovoltaic energy generation and prediction are crucial for the integration between solar plants and smart grid. Accurate solar radiation prediction is one of the most important research topics for solar energy gene...
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Wireless sensor networks have been adopted widely in various application and these networks play crucial role in numerous real-time monitoring systems. However, the event occurrence, detection of event and localizing ...
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A wireless sensor network is a collection of small, low-power devices called sensors that are deployed in an area to monitor and gather data from the surrounding environment. sensors can be deployed in two type either...
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the integration of Internet of things (IoT) sensor data with Enterprise Resource Planning (ERP) systems has emerged as a pivotal technology-driven initiative, offering vast potential for process optimization, enhanced...
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ISBN:
(纸本)9798350385083;9798350385076
the integration of Internet of things (IoT) sensor data with Enterprise Resource Planning (ERP) systems has emerged as a pivotal technology-driven initiative, offering vast potential for process optimization, enhanced data-driven decision-making, and profound business impact. this research endeavors to delve into this integration, comprehensively examining the implications for organizations, with a practical project serving as a proof of concept. the study scrutinizes the intricacies of IoT sensor integration with ERP systems, shedding light on the optimization of business processes and the extraction of valuable data insights. In addition, the research extends its focus towards "smart vision" technologies, aiming to achieve a higher level of automation and real-time decision support. the core of this research lies in the practical project, where a proof of concept is executed to integrate temperature sensors withthe Odoo ERP system. this project serves as a real-world demonstration of the integration's applicability and the tangible benefits it brings. By bridging the gap between theoretical concepts and practical implementation through this proof of concept, the study aims to provide actionable insights for organizations looking to harness the power of IoT sensor data, smart vision, and automation within their ERP systems. the outcomes of this research not only contribute to the growing body of knowledge on IoT-ERP integration but also provide a roadmap for organizations to leverage these technologies effectively in the modern business landscape.
the limitations of the networks of Internet of things (IoTs) and Wireless sensor Networks (WSNs) in terms of computational power, memory and connectivity give rise to several issues that need to be tackled, mostly dyn...
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ISBN:
(纸本)9781665495127
the limitations of the networks of Internet of things (IoTs) and Wireless sensor Networks (WSNs) in terms of computational power, memory and connectivity give rise to several issues that need to be tackled, mostly dynamically, to achieve their tasks. Definitively, a critical factor for the proper operation of these networks is to maintain the connectivity between the nodes, especially in a wireless mesh setting, where communication is performed in hop-by-hop fashion. A method that gains significant research interest for tackling the aforementioned issues is the employment of mobile nodes or as they are frequently called, mobile elements. In this work, we propose a scheme that utilizes carriers to transport mobile nodes to the required points in the network. We provide both a high level description of the concept and also a detailed algorithmic solution. the proposed solution is evaluated through a case study, where hot-spots are created due to congestion in the network and mobile elements are being used to resolve the problem. the experimental results demonstrate that the proposed algorithm can effectively restore the network operation. We believe that our proposed approach can be used to solve similar types of problems.
As deep neural networks continue to expand and become more complex, most edge devices are unable to handle their extensive processing requirements. therefore, the concept of distributed inference is essential to distr...
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ISBN:
(纸本)9798350333398
As deep neural networks continue to expand and become more complex, most edge devices are unable to handle their extensive processing requirements. therefore, the concept of distributed inference is essential to distribute the neural network among a cluster of nodes. However, distribution may lead to additional energy consumption and dependency among devices that suffer from unstable transmission rates. Unstable transmission rates harm real-time performance of IoT devices causing low latency, high energy usage, and potential failures. Hence, for dynamic systems, it is necessary to have a resilient DNN with an adaptive architecture that can downsize as per the available resources. this paper presents an empirical study that identifies the connections in ResNet that can be dropped without significantly impacting the model's performance to enable distribution in case of resource shortage. Based on the results, a multi-objective optimization problem is formulated to minimize latency and maximize accuracy as per available resources. Our experiments demonstrate that an adaptive ResNet architecture can reduce shared data, energy consumption, and latency throughout the distribution while maintaining high accuracy.
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