CITATION.cff

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title: >-
  Architecture of an Artificial Intelligence Model
  Manager for Event-Driven Component-Based SCADA
  Systems
message: To cite AIMM please use the following parameters
type: software
authors:
  - given-names: Zlatan Sičanica
    email: zlatan.sicanica@koncar.hr
    affiliation: Končar — Digital
    orcid: 'https://orcid.org/0000-0001-9731-3000'
  - given-names: Stjepan Sučić
    affiliation: Končar — Digital
  - given-names: Boris Milašinović
    affiliation: >-
      Faculty of Electrical Engineering and
      Computing, University of Zagreb
    orcid: 'https://orcid.org/0000-0002-7889-3131'
identifiers:
  - type: doi
    value: 10.1109/ACCESS.2022.3159715
  - type: url
    value: 'https://aimm.readthedocs.io/en/latest/'
repository-code: 'https://github.com/hat-open/aimm'
abstract: >-
  This paper analyzes Hat, an open-source framework
  for developing event-driven component-based SCADA
  applications, and discusses possibilities to add
  various analytical tools to such platforms. As a
  part of the contribution, an open-source component
  called Artificial Intelligence Model Manager (AIMM)
  has been developed and integrated into a Hat-based
  SCADA platform. AIMM is extensible through various
  plugins, allowing the addition of various models
  for advanced analytics e.g., machine learning
  tools, statistical tools, etc. The paper describes
  AIMM architecture and provides a use case in which
  state estimation was performed in a medium-voltage
  distribution grid. This case study demonstrates
  that it is possible to extend component-based SCADA
  systems with components for advanced analytics with
  minimal fundamental system changes.
keywords:
  - Artificial intelligence
  - Power system analysis compouting
  - SCADA systems
  - Software architecture
license: Apache-2.0