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repos: | ||
- repo: local | ||
hooks: | ||
- id: check | ||
name: check | ||
entry: doit check | ||
language: system | ||
types: [python] | ||
pass_filenames: false |
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# .readthedocs.yaml | ||
version: 2 | ||
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build: | ||
os: ubuntu-20.04 | ||
tools: | ||
python: "3.12" | ||
jobs: | ||
post_create_environment: | ||
# Install poetry | ||
# https://python-poetry.org/docs/#installing-manually | ||
- python -m pip install poetry | ||
post_install: | ||
# Install dependencies with 'docs' dependency group | ||
# https://python-poetry.org/docs/managing-dependencies/#dependency-groups | ||
- VIRTUAL_ENV=$READTHEDOCS_VIRTUALENV_PATH poetry install |
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# This CITATION.cff file was generated with cffinit. | ||
# Visit https://bit.ly/cffinit to generate yours today! | ||
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cff-version: 1.2.0 | ||
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: [email protected] | ||
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 |
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Contributing | ||
============ | ||
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Welcome to the contributing guidelines for the AIMM project. This document is | ||
intended for new contributors, to get acquainted with the contribution | ||
procedures. | ||
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||
This project is in early stages of development, with no exact functional | ||
specification (i.e., the current specification might be subject to changes). | ||
For this reason, pull requests are discouraged at this moment. | ||
|
||
Bug reports may be created using GitHub's issue tracker. However, the same | ||
warning as above applies, the issues might be declined. | ||
|
||
The issue tracker may also be used to ask questions about the project or | ||
suggest changes/new features. We will look into these and add them to our | ||
milestones, if accepted. Feel free to create a suggestion issue. The discussion | ||
is currently imagined to be in free-form, not enforcing any templates. |
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FROM python:3.10 | ||
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WORKDIR /opt/aimm | ||
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RUN pip install aimm | ||
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ENV PYTHONPATH=/opt/aimm | ||
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CMD ["aimm-server", "--conf", "aimm.yaml"] |
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Artificial Intelligence Model Manager | ||
===================================== | ||
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The Artificial Intelligence Model Manager (AIMM) project aims to provide | ||
resources for management of computational intelligence models. Using a | ||
plugin-based approach, it provides a services capable of: | ||
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* creating and storing models | ||
* fitting models | ||
* upload of already fitted models | ||
* data access | ||
* running the models | ||
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The server also has support for changeable frontend and persistence interfaces. | ||
This allows users to implement the ways server communicates to its clients | ||
(multiple parallel interfaces are supported) or stores the models. There are | ||
also default interfaces that are supported for both of these functions. | ||
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Installation | ||
------------ | ||
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AIMM is a Python (3.12 and newer) package containing implementations of the | ||
server implementation and some of its clients. It can be installed with the | ||
following command:: | ||
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pip install aimm | ||
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Development environment | ||
----------------------- | ||
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Development environment includes, besides the standard requirements of the base | ||
AIMM package, various tools and libraries that are used for the build process, | ||
documentation and testing. To set up the development environment, Python 3.12 | ||
and poetry are needed. Recommended way to set up is by running:: | ||
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python -m venv venv | ||
source venv/bin/activate | ||
pip install poetry | ||
poetry install | ||
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All other generic tasks like testing and documentation building are done | ||
through the build tool, use ``doit list`` to preview the complete list of all | ||
available tasks. |
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