EPOPTIS intends to design, implement and evaluate a secure platform that offers “Management-as-a-Service” for monitoring and managing heterogeneous Internet-of-Things (IoT) networks. The service will be provided by developing software and utilizing appropriate hardware for data collection, storage and processing, in order to make inference about network and device performance. Special focus will be put on interoperability of the service, in order to enable monitoring and managing IoT networks with heterogeneous hardware and software technologies. In addition, the project will develop user interfaces for visualizing collected data and data processing results.
EPOPTIS
“A Secure Platform for Efficient Management as a Service in the Internet of Things”
Category: National
Funding Agency: funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund)
Programme: Single RTDI State Aid Action “RESEARCH – CREATE – INNOVATE”
Coordinator: FORTH
Start Date: 19.09.2019
Expiration Date: 18.03.2022
Duration: 30 months
Related URL: http://www.epoptis-project.gr/en/home/
Partners: Future Intelligence Telecom Engineering Company
Funding Agency: funded by the Operational Programme “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014-2020) and co-financed by Greece and the European Union (European Regional Development Fund)
Programme: Single RTDI State Aid Action “RESEARCH – CREATE – INNOVATE”
Coordinator: FORTH
Start Date: 19.09.2019
Expiration Date: 18.03.2022
Duration: 30 months
Related URL: http://www.epoptis-project.gr/en/home/
Partners: Future Intelligence Telecom Engineering Company
Description:
Objectives:
EPOPTIS has the following main objectives:
- Design, implement, and evaluate an interoperable and secure platform for providing Management-as-a-Service for IoT networks.
- Develop data collection and visualization techniques for heterogeneous data generated by IoT networks.
- Utilize statistical methods and machine learning algorithms for processing collected data and automatically detecting and predicting faults in IoT networks.