Publication Details
Developing a Data Analytics Toolbox to Support CPS-based Services
Molina Ruiz Enriqueta (UGR)
Rodriguez González Alejandro (UPN)
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT)
Wendt Juana (VOLKSWAGEN AG (VW))
Wolfe Christian (DUKE)
Zanin Massimiliano (UPN)
artificial intelligence, data analytics, cyber-physical systems
The fast growth of Cyber-Physical Systems (CPSs) has brought us new opportunities to benefit from ever-increasing quantities of data describing our environment and behaviours. These data have a strong potential to become the basis of novel innovative services and products. However, the nature of CPS data streams makes it challenging to apply known data analytics methods and tools in an efficient way. This contribution discusses these challenges and shows how they could be tackled. Specifically, we present the initial development of a Data Analytics Toolbox designed to deal with some of them, like the streaming nature of the information they provide, and the need for efficient filtering techniques. As a case study, we further describe an application of the toolbox based on a real business case, aimed at improving high resolution weather forecast models.
@INPROCEEDINGS{FITPUB12713, author = "A. Elisa Herrmann and Enriqueta Ruiz Molina and Alejandro Gonz\'{a}lez Rodriguez and Pavel Smr\v{z} and Juana Wendt and Christian Wolfe and Massimiliano Zanin", title = "Developing a Data Analytics Toolbox to Support CPS-based Services", pages = "58--64", booktitle = "Mediterranean Conference on Embedded Computing", year = 2020, location = "New York, US", publisher = "IEEE Biometric Council", ISBN = "978-1-7281-6949-1", doi = "10.1109/MECO49872.2020.9134351", language = "english", url = "https://www.fit.vut.cz/research/publication/12713" }