In the era of big data, the construction of intelligent teaching space model based on cloud edge data collaboration is the focus of current education innovation exploration. On the basis of understanding the construct...
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This research discusses about the design and execution of a direct current (DC) microgrid system that leverages Internet of Things (IoT) technology. The microgrid combines various green energy sources, including solar...
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ISBN:
(数字)9798350368413
ISBN:
(纸本)9798350368420
This research discusses about the design and execution of a direct current (DC) microgrid system that leverages Internet of Things (IoT) technology. The microgrid combines various green energy sources, including solar panels, a wind turbine, and a DC generator, along with a battery storage unit. A microcontroller serves as the core control unit, controlling and regulating power flow. The system gives real-time data collection for performance study through IoT integration. The collected data reveals the effectiveness of the DC microgrid system, with solar energy presenting as the most reliable renewable source. The application of IoT-based control indicates the promise for intelligent and sustainable energy management. This study paves the way for advancements in microgrid technology, merging artificial intelligence, wireless energy harvesting for improved performance and peer-to-peer energy sharing.
intelligent edge orchestration has become a vital component within next generation communication networks, such as 5G. They offer optimal resource allocation and service distribution, hence allow for full utilization ...
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Today design-manufacturing industry is automated and digital, where machines communicate with every other. A clever factory equipped with statistics alternate in industrial, the Internet of Things (IoT) is the forthco...
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This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit cu...
This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..
Infrastructure is becoming smarter due to technical advances such as the Internet of Things (IoT) that enables a greater interconnectivity between assets and Artificial Intelligence (AI) to enhance the decision making...
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With the rapid developoment of Internet of Things technology, in the filed intelligent envieronmental protection, a large number. of ens iron menial protection equipment access, Ill us will produce hundreds of million...
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ISBN:
(纸本)9781728183190
With the rapid developoment of Internet of Things technology, in the filed intelligent envieronmental protection, a large number. of ens iron menial protection equipment access, Ill us will produce hundreds of millions of enivironmental data. The traditional data processing mode of cloud computing is difficult to meet the demand of intelligent analysis, and a new kind of Internet of things technology - edge computing is gradually concerned by people. The proposal of edge computing is mainly to relive to the data processing pressure generated by hundreds of millions of iot devices. Edge computing technology has been applied in many fields. The application of edge computing technology in the field of environmental protection can accelerate the landing applications in the intelligent environmental protection industry und holier promote the intelligent environmental protection. This paper mainly studies the edge computing technology is applied in environmental wisdom, through a comprehensive study reference architecture model, and calculate the edge of the architectural model in practical application, design a kind of wisdom were calculated based ion edge iot framework of environmental and on this basis, combining With century oasis software and systems engineering technology I projects, design a kind of wisdom environmental oriented iot gateway software architecture, and finally reality the edge (of. the Internet if things intelligent gateway for wisdom of environmental protection. The research focuses ion the problems of intelligent access toen;environmental protection devices, safe transmission of environmental protection data, quick connection of en;iron mental protection platform und so on. Finally, it is tested in a practical project to verify. the stability and reliability of intelligent;listen ay on the edge of smart environmental protection. System evaluation results shim that the wisdom green edge intelligent galena, support for multiple ty(pes of environmenta
The Internet of things (IoT) is leading towards revolutionary applications with huge potential to improvise the efficiency of industries and environment multifold. Applications of IoT are marking their presence using ...
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ISBN:
(纸本)9783030823221;9783030823214
The Internet of things (IoT) is leading towards revolutionary applications with huge potential to improvise the efficiency of industries and environment multifold. Applications of IoT are marking their presence using the concept of a remote monitoring system, real-time data, visualization of data, and dataanalytics. This paper proposes and simulate an IoT based application of an intelligent Light Control System. Luminosity sensors are used which sense the lux value. The application of light control system uses the lux value to control the switch ON/OFF of LED, remotely using the Constrained Application Protocol (CoAP protocol) at the application layer. The application is simulated in Cooj a simulator along with Add-on plug-in Copper (Cu) in the Firefox browser. In this application, LEDs are switched ON/OFF automatically depending upon the availability of sunlight. The aim of this simulation is towards humungous power saving which will be a step forward to a green environment.
With the development of digital media technology, the concepts of a smart earth and a smart city have been gradually recognized. In recent years, smart tourism has gained much more attention. smart tourism is the prod...
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The H2020 DEMETER project uses advanced AI and IoT technologies in order to promote the sustainability of the agricultural sector, to decrease the costs and the environmental impact, while maintaining yields at the sa...
The H2020 DEMETER project uses advanced AI and IoT technologies in order to promote the sustainability of the agricultural sector, to decrease the costs and the environmental impact, while maintaining yields at the same time. To achieve this it developed a service-oriented architecture where various interoperable enablers (i.e., services) can be combined in order to create apps that optimize the usage of resources and yield at the same time. This paper first presents a specific use-case that optimizes rice and maize irrigation and fertilization management processes. Then, it focuses its main part in the development of a data fusion enabler that, combined with appropriate sensor, dataanalytics, decision support and actuation enablers was combined into the development of DEMETER apps for this use case, that achieved reductions of the used resources (water and fertilizer) while maintaining the crop yields. For the development of this fusion enabler, several preexisting fusion techniques were examined, and the most appropriate of these were used and combined to form the fusion enabler.
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