Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence

Mateusz Kalinowski; Paweł Weichbroth

doi:10.15611/ie.2022.1.02

Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence

Abstract

Research, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning (artificial intelligence), computational intelligence, and database management systems (DBMS). As nowadays, a numerous of the RDI projects are oriented towards the development of data intensive solutions, the authors are confident that these lessons will be valuable not only for data engineers, but also for those researchers and practitioners who are dealing with the issues related to building and validating machine learning models, applications of moving averages to high-frequency data streams, and the implementation and deployment of DBMS.

Citations

0

CrossRef
0

Web of Science
0

Scopus

Authors (2)

Mateusz Kalinowski
Paweł Weichbroth dr

Cite as

Full text

download paper

downloaded 69 times

Publication version: Accepted or Published Version
DOI:: Digital Object Identifier (open in new tab) 10.15611/ie.2022.1.02
License: open in new tab

full content of the article see on external site open in new tab

Keywords

Details

Category:

Articles

Type:

artykuły w czasopismach

Published in:

Informatyka Ekonomiczna. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu pages 9 - 19,
ISSN: 1507-3858

Language:

English

Publication year:

2022

Bibliographic description:

Kalinowski M., Weichbroth P.: Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence// Informatyka Ekonomiczna. Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu -,iss. 1(63) (2022), s.9-19

DOI: