scholarly journals A unified ontology-based data integration approach for the internet of things

Author(s):  
Ahmed Swar ◽  
Ghada Khoriba ◽  
Mohamed Belal

<span lang="EN-US">Data integration enables combining data from various data sources in a standard format. Internet of things (IoT) applications use ontology approaches to provide a machine-understandable conceptualization of a domain. We propose a unified ontology schema approach to solve all IoT integration problems at once. The data unification layer maps data from different formats to data patterns based on the unified ontology model. This paper proposes a middleware consisting of an ontology-based approach that collects data from different devices. IoT middleware requires an additional semantic layer for cloud-based IoT platforms to build a schema for data generated from diverse sources. We tested the proposed model on real data consisting of approximately 160,000 readings from various sources in different formats like CSV, JSON, raw data, and XML. The data were collected through the file transfer protocol (FTP) and generated 960,000 resource description framework (RDF) triples. We evaluated the proposed approach by running different queries on different machines on SPARQL protocol and RDF query language (SPARQL) endpoints to check query processing time, validation of integration, and performance of the unified ontology model. The average response time for query execution on generated RDF triples on the three servers were approximately 0.144 seconds, 0.070 seconds, 0.062 seconds, respectively.</span>

2018 ◽  
Vol 10 (8) ◽  
pp. 2613
Author(s):  
Dandan He ◽  
Zhongfu Li ◽  
Chunlin Wu ◽  
Xin Ning

Industrialized construction has raised the requirements of procurement methods used in the construction industry. The rapid development of e-commerce offers efficient and effective solutions, however the large number of participants in the construction industry means that the data involved are complex, and problems arise related to volume, heterogeneity, and fragmentation. Thus, the sector lags behind others in the adoption of e-commerce. In particular, data integration has become a barrier preventing further development. Traditional e-commerce platform, which considered data integration for common product data, cannot meet the requirements of construction product data integration. This study aimed to build an information-integrated e-commerce platform for industrialized construction procurement (ICP) to overcome some of the shortcomings existing platforms. We proposed a platform based on Building Information Modelling (BIM) and linked data, taking an innovative approach to data integration. It uses industrialized construction technology to support product standardization, BIM to support procurement process, and linked data to connect different data sources. The platform was validated using a case study. With the development of an e-commerce ontology, industrialized construction component information was extracted from BIM models and converted to Resource Description Framework (RDF) format. Related information from different data sources was also converted to RDF format, and Simple Protocol and Resource Description Framework Query Language (SPARQL) queries were implemented. The platform provides a solution for the development of e-commerce platform in the construction industry.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peter Baumann ◽  
Dimitar Misev ◽  
Vlad Merticariu ◽  
Bang Pham Huu

AbstractMulti-dimensional arrays (also known as raster data or gridded data) play a key role in many, if not all science and engineering domains where they typically represent spatio-temporal sensor, image, simulation output, or statistics “datacubes”. As classic database technology does not support arrays adequately, such data today are maintained mostly in silo solutions, with architectures that tend to erode and not keep up with the increasing requirements on performance and service quality. Array Database systems attempt to close this gap by providing declarative query support for flexible ad-hoc analytics on large n-D arrays, similar to what SQL offers on set-oriented data, XQuery on hierarchical data, and SPARQL and CIPHER on graph data. Today, Petascale Array Database installations exist, employing massive parallelism and distributed processing. Hence, questions arise about technology and standards available, usability, and overall maturity. Several papers have compared models and formalisms, and benchmarks have been undertaken as well, typically comparing two systems against each other. While each of these represent valuable research to the best of our knowledge there is no comprehensive survey combining model, query language, architecture, and practical usability, and performance aspects. The size of this comparison differentiates our study as well with 19 systems compared, four benchmarked to an extent and depth clearly exceeding previous papers in the field; for example, subsetting tests were designed in a way that systems cannot be tuned to specifically these queries. It is hoped that this gives a representative overview to all who want to immerse into the field as well as a clear guidance to those who need to choose the best suited datacube tool for their application. This article presents results of the Research Data Alliance (RDA) Array Database Assessment Working Group (ADA:WG), a subgroup of the Big Data Interest Group. It has elicited the state of the art in Array Databases, technically supported by IEEE GRSS and CODATA Germany, to answer the question: how can data scientists and engineers benefit from Array Database technology? As it turns out, Array Databases can offer significant advantages in terms of flexibility, functionality, extensibility, as well as performance and scalability—in total, the database approach of offering “datacubes” analysis-ready heralds a new level of service quality. Investigation shows that there is a lively ecosystem of technology with increasing uptake, and proven array analytics standards are in place. Consequently, such approaches have to be considered a serious option for datacube services in science, engineering and beyond. Tools, though, vary greatly in functionality and performance as it turns out.


2021 ◽  
pp. 1-14
Author(s):  
Fen Li ◽  
Oscar Sanjuán Martínez ◽  
R.S. Aiswarya

BACKGROUND: The modern Internet of Things (IoT) makes small devices that can sense, process, interact, connect devices, and other sensors ready to understand the environment. IoT technologies and intelligent health apps have multiplied. The main challenges in the sports environment are playing without injuries and healthily. OBJECTIVE: In this paper the Internet of Things-based Smart Wearable System (IoT-SWS) is introduced for monitoring sports person activity to improve sports person health and performance in a healthy way. METHOD: Wearable systems are commonly used to capture individual sports details on a real-time basis. Collecting data from wearable devices and IoT technologies can help organizations learn how to optimize in-game strategies, identify opponents’ vulnerabilities, and make smarter draft choices and trading decisions for a sportsperson. RESULTS: The experimental result shows that IoT-SWS achieve the highest accuracy of 98.22% and efficient in predicting the sports person’s health to improve sports person performance reliably.


2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
Kwang-il Hwang ◽  
Sung-wook Nam

In order to construct a successful Internet of things (IoT), reliable network construction and maintenance in a sensor domain should be supported. However, IEEE 802.15.4, which is the most representative wireless standard for IoT, still has problems in constructing a large-scale sensor network, such as beacon collision. To overcome some problems in IEEE 802.15.4, the 15.4e task group proposed various different modes of operation. Particularly, the IEEE 802.15.4e deterministic and synchronous multichannel extension (DSME) mode presents a novel scheduling model to solve beacon collision problems. However, the DSME model specified in the 15.4e draft does not present a concrete design model but a conceptual abstract model. Therefore, in this paper we introduce a DSME beacon scheduling model and present a concrete design model. Furthermore, validity and performance of DSME are evaluated through experiments. Based on experiment results, we analyze the problems and limitations of DSME, present solutions step by step, and finally propose an enhanced DSME beacon scheduling model. Through additional experiments, we prove the performance superiority of enhanced DSME.


Author(s):  
Zhiping Wang ◽  
Xinxin Zheng ◽  
Zhichen Yang

The Internet of Things (IoT) technology is an information technology developed in recent years with the development of electronic sensors, intelligence, network transmission and control technologies. This is the third revolution in the development of information technology. This article aims to study the algorithm of the Internet of Things technology, through the investigation of the hazards of athletes’ sports training, scientifically and rationally use the Internet of Things technology to collect data on safety accidents in athletes’ sports training, thereby reducing the risk of athletes’ sports training and making athletes better. In this article, the methods of literature research, analysis and condensing, questionnaire survey, theory and experiment combination, etc., investigate the safety accident data collection of the Internet of Things technology in athletes’ sports training, and provide certain theories and methods for future in-depth research practice basis. The experimental results in this article show that 82% of athletes who are surveyed under the Internet of Things technology will have partial injuries during training, reducing the risk of safety accidents in athletes’ sports training, and better enabling Chinese athletes to achieve a consistent level of competition and performance through a virtuous cycle of development.


2020 ◽  
Vol 1 (3) ◽  
pp. 333-350
Author(s):  
Yuto Tsukagoshi ◽  
Takahiro Kawamura ◽  
Yuichi Sei ◽  
Yasuyuki Tahara ◽  
Akihiko Ohsuga

A number of urban challenges are encountered by modern societies. Governments, businesses and public bodies need to make statistical data widely available in order to tackle these challenges. Nonetheless, current literature and data are problematic; they have inaccuracies which lead to less effective methods of resolving these issues. This research aims to solve this challenge by thinking of a university campus as a microcosm of society, implementing a data integration schema, and combining data into a knowledge graph. Existing completion methods will then be applied and updated. Especially in regards to bicycle environment, our knowledge graph was tailored and evaluated in line with conventional methods, and secondly with our proposed derivative methods. Roughly 650 pieces of parking data, with various dates and times, was contrasted with each time's mean absolute error. Our approach accurately projected 54.5 more bicycles than the conventional method.


2018 ◽  
Vol 2 ◽  
pp. e25614 ◽  
Author(s):  
Florian Pellen ◽  
Sylvain Bouquin ◽  
Isabelle Mougenot ◽  
Régine Vignes-Lebbe

Xper3 (Vignes Lebbe et al. 2016) is a collaborative knowledge base publishing platform that, since its launch in november 2013, has been adopted by over 2 thousand users (Pinel et al. 2017). This is mainly due to its user friendly interface and the simplicity of its data model. The data are stored in MySQL Relational DBs, but the exchange format uses the TDWG standard format SDD (Structured Descriptive DataHagedorn et al. 2005). However, each Xper3 knowledge base is a closed world that the author(s) may or may not share with the scientific community or the public via publishing content and/or identification key (Kopfstein 2016). The explicit taxonomic, geographic and phenotypic limits of a knowledge base are not always well defined in the metadata fields. Conversely terminology vocabularies, such as Phenotype and Trait Ontology PATO and the Plant Ontology PO, and software to edit them, such as Protégé and Phenoscape, are essential in the semantic web, but difficult to handle for biologist without computer skills. These ontologies constitute open worlds, and are expressed themselves by RDF triples (Resource Description Framework). Protégé offers vizualisation and reasoning capabilities for these ontologies (Gennari et al. 2003, Musen 2015). Our challenge is to combine the user friendliness of Xper3 with the expressive power of OWL (Web Ontology Language), the W3C standard for building ontologies. We therefore focused on analyzing the representation of the same taxonomic contents under Xper3 and under different models in OWL. After this critical analysis, we chose a description model that allows automatic export of SDD to OWL and can be easily enriched. We will present the results obtained and their validation on two knowledge bases, one on parasitic crustaceans (Sacculina) and the second on current ferns and fossils (Corvez and Grand 2014). The evolution of the Xper3 platform and the perspectives offered by this link with semantic web standards will be discussed.


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