3 research outputs found
IIoT Data Ness: From Streaming to Added Value
In the emerging Industry 4.0 paradigm, the internet of things has been an innovation driver, allowing for
environment visibility and control through sensor data analysis. However the data is of such volume and
velocity that data quality cannot be assured by conventional architectures. It has been argued that the
quality and observability of data are key to a project’s success, allowing users to interact with data more
effectively and rapidly. In order for a project to become successful in this context, it is of imperative
importance to incorporate data quality mechanisms in order to extract the most value out of data. If this
goal is achieved one can expect enormous advantages that could lead to financial and innovation gains
for the industry. To cope with this reality, this work presents a data mesh oriented methodology based
on the state-of-the-art data management tools that exist to design a solution which leverages data quality
in the Industrial Internet of Things (IIoT) space, through data contextualization. In order to achieve this
goal, practices such as FAIR data principles and data observability concepts were incorporated into the
solution. The result of this work allowed for the creation of an architecture that focuses on data and
metadata management to elevate data context, ownership and quality.O conceito de Internet of Things (IoT) é um dos principais fatores de sucesso para a nova Indústria 4.0. Através de análise de dados sobre os valores que os sensores coletam no seu ambiente, é possÃvel a construção uma plataforma capaz de identificar condições de sucesso e eventuais problemas antes que estes ocorram, resultando em ganho monetário relevante para as empresas. No entanto, este caso de uso não é de fácil implementação, devido à elevada quantidade e velocidade de dados proveniente de um ambiente de IIoT (Industrial Internet of Things)
Symposium Proceedings—Coyotes in the Southwest: A Compendium of Our Knowledge [complete work, 185 pp.]
This is the complete volume, containing all 40+ articles and presentations. Each article is also hosted here separately under its individual title and authors
2006-2007 Louisiana Tech University Catalog
The Louisiana Tech University Catalog includes announcements and course descriptions for courses offered at Louisiana Tech University for the academic year of 2006-2007.https://digitalcommons.latech.edu/university-catalogs/1008/thumbnail.jp