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.
the concept of Edge-cloud Continuum (ECC) serves as a strategic infrastructure for deploying modern Collective-adaptive systems (CASs). In this framework, heterogeneous devices create a continuum between the edge and ...
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ISBN:
(纸本)9798350389777;9798350389760
the concept of Edge-cloud Continuum (ECC) serves as a strategic infrastructure for deploying modern Collective-adaptive systems (CASs). In this framework, heterogeneous devices create a continuum between the edge and the cloud, offering new opportunities and challenges for deploying collective systems such as smart cities, IoT applications, and more. Preliminary work, like the pulverisation approach, models a system as an ensemble of logical entities connected forming a dynamic graph, where each device is decomposed into five independent components (i.e., sensors, actuators, state, communication, and behaviour). this approach addresses the challenge of devising an application partitioning strategy to effectively deploy collective systems in the continuum but does not provide an explicit mechanism to handle dynamic system reconfiguration. For this reason, learning approaches can be effective in managing the dynamic and continuously evolving requirements of the ECC (e.g., latency, power consumption, computational resources). In this paper we propose a new generation of "Intelligent Collective Services" that uses advanced partitioning models and learning approaches, such as Graph Neural Network (GNN) and Many-agent Reinforcement Learning (MARL), to enhance adaptability and pave the way for the next generation of CAS in the ECC.
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.
the integration of multiple sensors and advanced technologies in the field of vehicle safety and security has emerged as a promising approach to enhance overall road safety and protect vehicles from potential threats....
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Forest fires present a significant hazard to property, lives, and ecosystems globally, necessitating swift detection and containment measures. Historically, manual forest fire control systems relied on human observati...
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Geo-location, also known as measurement report (MR) location, is a technique to determine the geographic location of user equipment (UE) and the behaviour attribute of telephone traffic based on wireless signals measu...
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Wireless sensor (WS) is widely used in the state monitoring of complex systems, and the health state of WS is of great significance to ensure the stability of complex systems. Considering the problems of diverse indic...
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the challenging tasks of the precision agriculture require an extended study of novel equipment and comprehensive selection of particular sensors and sensorsystems. Drones are powered by batteries which makes them se...
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the paper analyses the main problems of the use of electric energy, taking into account the trends of the evolution of modern electric power systems. Arguments are given in favour of the intensive development of a dis...
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