A Smart Campus Prototype for Demonstrating the Semantic Integration of Heterogeneous Data

Boran, Aidan; Bedini, Ivan; Matheus, Christopher J.; Patel‐Schneider, Peter F.; Keeney, John

doi:10.1007/978-3-642-23580-1_18

Cited by 10 publications

(9 citation statements)

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“…There is important information about the use of specialized AI techniques in user interaction and that they learn from each interaction [18]. These models are robust and contribute significantly to the development of this work [19]. Based on the review carried out, it can be highlighted that the proposed work differs from those existing in the integration of two technologies, such as AI and data analysis, in a single environment.…”

Section: Related Workmentioning

confidence: 99%

“…In addition, the teacher becomes the entity that determines what they should learn and how they should do it. For this reason, the teacher has a greater influence in identifying the performance of each student [19]. Therefore, this identification is biased to the teacher's criteria, a factor that is not expected in an ideal learning model.…”

Section: Identification Of the Environmentmentioning

confidence: 99%

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Improvement of an Online Education Model with the Integration of Machine Learning and Data Analysis in an LMS

2020

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The events that took place in the year 2020 have shown us that society is still fragile and that it is exposed to events that rapidly change the paradigms that govern it. This has been shown by a pandemic like Coronavirus disease 2019; this global emergency has changed the way people interact, communicate, study, or work. In short, the way in which society carries out all activities has changed. This includes education, which has bet on the use of information and communication technologies to reach students. An example of the aforementioned is the use of learning management systems, which have become ideal environments for resource management and the development of activities. This work proposes the integration of technologies, such as artificial intelligence and data analysis, with learning management systems in order to improve learning. This objective is outlined in a new normality that seeks robust educational models, where certain activities are carried out in an online mode, surrounded by technologies that allow students to have virtual assistants to guide them in their learning.

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Section: Related Workmentioning

confidence: 99%

Section: Identification Of the Environmentmentioning

confidence: 99%

Improvement of an Online Education Model with the Integration of Machine Learning and Data Analysis in an LMS

2020

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“…There is an even growing literature for Smart Campuses which are related to data integration and real-time processing of massive heterogeneous data sources. An application prototype using semantic technologies is discussed in (Boran et al, 2011). The idea behind this approach is to include semantic information using ontologies with OWL and SPARQL.…”

Section: Smart Campusmentioning

confidence: 99%

Extensible Data Management Architecture for Smart Campus Applications - A Crowdsourcing based Solution

Adamkó

Kollár

2014

Proceedings of the 10th International Conference on Web Information Systems and Technologies

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The technological advancements that have occurred during the past decade in various domains, including sensors, wireless communications, location positioning technologies and the web, allow the collection of a wide range of data. Possible sources of that data include intelligent devices (smartphones, tablets, etc.) containing various sensors, Web pages, and social networking sites. Collected data are subject to analysis (using data mining or pattern recognition approaches, for instance) and after processing new content might be inferred. This is a value-added service that can itself be used as a data source. In this paper, we use our University Campus as an example for establishing a data management architecture that integrates into a more general, extensible publish/subscribe based model of crowdsourced applications.

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“…At present, university campuses recognize the integration of technologies as a path that leads them to digital transformation. Many of these campuses even work to consolidate information and communication technologies (ICT) on this basis, leading them to be considered as intelligent campuses [1]. Creating a comfortable, sustainable, and safe environment is characteristic a smart campus, which efficiently contributes to the development of learning and the administrative management of the campus [2].…”

Section: Introductionmentioning

confidence: 99%

Application of a Big Data Framework for Data Monitoring on a Smart Campus

et al. 2019

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At present, university campuses integrate technologies such as the internet of things, cloud computing, and big data, among others, which provide support to the campus to improve their resource management processes and learning models. Integrating these technologies into a centralized environment allows for the creation of a controlled environment and, subsequently, an intelligent environment. These environments are ideal for generating new management methods that can solve problems of global interest, such as resource consumption. The integration of new technologies also allows for the focusing of its efforts on improving the quality of life of its inhabitants. However, the comfort and benefits of technology must be developed in a sustainable environment where there is harmony between people and nature. For this, it is necessary to improve the energy consumption of the smart campus, which is possible by constantly monitoring and analyzing the data to detect any anomaly in the system. This work integrates a big data framework capable of analyzing the data, regardless of its format, providing effective and efficient responses to each process. The method developed is generic, which allows for its application to be adequate in addressing the needs of any smart campus.

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A Smart Campus Prototype for Demonstrating the Semantic Integration of Heterogeneous Data

Cited by 10 publications

References 1 publication

Improvement of an Online Education Model with the Integration of Machine Learning and Data Analysis in an LMS

Improvement of an Online Education Model with the Integration of Machine Learning and Data Analysis in an LMS

Extensible Data Management Architecture for Smart Campus Applications - A Crowdsourcing based Solution

Application of a Big Data Framework for Data Monitoring on a Smart Campus

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