Judvaitis J, Blumbergs E, Arzovs A, Mackus AI, Balass R, Selavo L. . A Set of Tools and Data Management Framework for the IoT–Edge–Cloud Continuum. Applied System Innovation (ISSN 2571-5577), 2024, 7(6), MDPI, 2024.
Bibtex citāts:
Bibtex citāts:
@article{19847_2024,
author = {Judvaitis J and Blumbergs E and Arzovs A and Mackus AI and Balass R and Selavo L. },
title = {A Set of Tools and Data Management Framework for the IoT–Edge–Cloud Continuum},
journal = {Applied System Innovation (ISSN 2571-5577), 2024},
volume = {7},
issue = {6},
publisher = {MDPI},
year = {2024}
}
author = {Judvaitis J and Blumbergs E and Arzovs A and Mackus AI and Balass R and Selavo L. },
title = {A Set of Tools and Data Management Framework for the IoT–Edge–Cloud Continuum},
journal = {Applied System Innovation (ISSN 2571-5577), 2024},
volume = {7},
issue = {6},
publisher = {MDPI},
year = {2024}
}
Anotācija: Developing and managing complex IoT–Edge–Cloud Continuum (IECC) systems are challenging due to the system complexity and diversity. Internet of Things (IoT), Edge, and Cloud components combined with artificial intelligence (AI) in data processing systems must ensure strong security and privacy for data sources. The approach of the IECC Data Management Framework (DMF) introduces a novel combination of multiple easy-to-configure plugin environments using data visualization features. These contributions collectively address the critical challenges inherent in heterogeneous environments such as scalability, data privacy, and configuration management by standardizing data flow configurations and increasing stakeholder trust in sensitive applications, particularly in critical infrastructure monitoring.