Cloud computing and semantic web technologies for ubiquitous management of smart cities-related competences

Iatrellis, Omiros; Panagiotakopoulos, Theodor; Gerogiannis, Vassilis C.; Fitsilis, Panos; Kameas, Achilles

doi:10.1007/s10639-020-10351-9

Cited by 19 publications

(9 citation statements)

References 18 publications

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“…The authors also conducted simulation experiments to evaluate the proposed method's performance and compared it to other existing methods, demonstrating its effectiveness in terms of data accuracy, security, and energy efficiency. Iatrellis et al [22] proposed a new approach to managing smart city-related competencies that makes use of cloud computing and semantic web technologies. The authors discuss the increasing complexity of smart cities necessitating a more efficient method of managing competencies across multiple domains and stakeholders.…”

Section: Related Workmentioning

confidence: 99%

Join Operation for Semantic Data Enrichment of Asynchronous Time Series Data

Garcia

Peyman

Piè

et al. 2023

Axioms

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In this paper, we present a novel framework for enriching time series data in smart cities by supplementing it with information from external sources via semantic data enrichment. Our methodology effectively merges multiple data sources into a uniform time series, while addressing difficulties such as data quality, contextual information, and time lapses. We demonstrate the efficacy of our method through a case study in Barcelona, which permitted the use of advanced analysis methods such as windowed cross-correlation and peak picking. The resulting time series data can be used to determine traffic patterns and has potential uses in other smart city sectors, such as air quality, energy efficiency, and public safety. Interactive dashboards enable stakeholders to visualize and summarize key insights and patterns.

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Section: Related Workmentioning

confidence: 99%

Join Operation for Semantic Data Enrichment of Asynchronous Time Series Data

Garcia

Peyman

Piè

et al. 2023

Axioms

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“…Using the mass storage services and software support services provided by the cloud platform, system development can be carried out quickly and the development cycle can be shortened. Based on the above reasons, it is a better choice to use the cloud computing platform to build the school's self-built educational administration system [20,21].…”

Section: Advantages Of Cloud Computing Modelmentioning

confidence: 99%

University Educational Administration Management Platform Integrating Distributed Real-time Cloud Computing System

Miao

2022

Mathematical Problems in Engineering

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The prosperity of the economy has made the society develop rapidly, and the traditional education management system can no longer meet the needs of the modern society. Under the background of college enrollment expansion, it has brought new challenges to school management and development. In recent years, the evolution and widespread adoption of virtualization, service-oriented architecture, autonomous, and utility computing have converged to give birth to a new paradigm: cloud computing. Cloud computing allows on-demand delivery of software, hardware, and data as a service. Cloud computing has the characteristics of massive processing and storage capacity, high efficiency, virtualization, and low cost. It has changed the traditional way of accessing software and hardware, providing users with convenient services and computing resources, which has achieved remarkable results in the related fields. Meanwhile, cloud computing plays an important role in education and teaching through its wide application in various fields. Based on this, this paper aims to study the application of distributed real-time cloud computing system in educational administration management in colleges and universities. This paper establishes a university educational administration management platform based on the cloud service computing system, and applies the management technology and distributed storage technology of the cloud computing platform. The system constructed in this paper significantly improves the utilization of CPU and memory. The research results of this paper showed that the response speed of the educational administration management system built through cloud computing has been significantly improved, with an average response time of 1.3s and an error of less than 0.4.

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“…Iatrellis et al [41] proposed an ontology that incorporates the relevant knowledge and a rule-base for modeling the phases of an employee training process to make up the learning platform's semantic architecture. The semantic model has been translated into a relational database schema, which is then used by the system to execute meaningful queries in order to improve competence management efficiency.…”

Section: Smart Cities and Smart Agriculturementioning

confidence: 99%

Semantic Web and Internet of Things: Challenges, Applications and Perspectives

Amara

Hemam

Djezzar

et al. 2022

JICTS

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The apparent growth of the internet of things (IoT) has allowed its deployment in many domains. The IoT devices sense their surroundings and transmit the data via the Web. According to statistics, due to the proliferation of smart devices, the number of active IoT devices is expected to exceed 25.4 billion by 2030.1 A large number of IoT objects gather an enormous amount of raw data. The data generated by various IoT objects and sensors are heterogeneous, with varying types and formats. Therefore, it is difficult for IoT systems to share and reuse raw IoT data, which causes the problem of lack of interoperability. The lack of interoperability in IoT systems creates a problematic issue that prevents IoT systems from performing well. To address this issue, data modeling and knowledge representation using semantic web technologies may be an appropriate solution to give meaning to raw IoT data and convert it to an enriched data format. The primary goal of this research section is to highlight the best outcomes for semantic interoperability among IoT systems, which can serve as a guideline for future studies via the presentation of a literature review on semantic interoperability for Internet of Things systems, including challenges, prospects, and recent work. The paper also provides an overview of the application of semantic web technologies in IoT systems, such as specific ontologies, frameworks, and application domains that use semantic technologies in the IoT areas to solve interoperability and heterogeneity problems.

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Cloud computing and semantic web technologies for ubiquitous management of smart cities-related competences

Cited by 19 publications

References 18 publications

Join Operation for Semantic Data Enrichment of Asynchronous Time Series Data

Join Operation for Semantic Data Enrichment of Asynchronous Time Series Data

University Educational Administration Management Platform Integrating Distributed Real-time Cloud Computing System

Semantic Web and Internet of Things: Challenges, Applications and Perspectives

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