Skip to main content

CircleCI pipeline status badge ReadTheDocs badge pypi PyPI - license badge DOI

Multi-Agent System for IIoT

agentMET4FOF is an implementation of a multi-agent system for agent-based analysis and processing of both static data sets and data streams with IIoT applications in mind. More on the motivation that drives the project can be found in the section About.

Table of content

💫Quickstart

agentMET4FOF comes bundled with some tutorials to get you started as quick as possible. In your Python console execute the following to run the first tutorial.

>>> from agentMET4FOF_tutorials.tutorial_1_generator_agent import demonstrate_generator_agent_use
>>> generator_agent_network = demonstrate_generator_agent_use()
Starting NameServer...
Broadcast server running on 0.0.0.0:9091
NS running on 127.0.0.1:3333 (127.0.0.1)
URI = PYRO:Pyro.NameServer@127.0.0.1:3333

--------------------------------------------------------------
|                                                            |
| Your agent network is starting up. Open your browser and   |
| visit the agentMET4FOF dashboard on http://127.0.0.1:8050/ |
|                                                            |
--------------------------------------------------------------

INFO [2021-02-05 18:12:52.277759] (SineGeneratorAgent_1): INITIALIZED
INFO [2021-02-05 18:12:52.302862] (MonitorAgent_1): INITIALIZED
[2021-02-05 18:12:52.324078] (SineGeneratorAgent_1): Connected output module: MonitorAgent_1
SET STATE:   Running
[...]
>>> generator_agent_network.shutdown()
0
NS shut down.

💬About

Sensor deployments in industrial applications usually form networks in all sorts of environments. This requires a flexible framework for the implementation of the corresponding data analysis. An excellent way to represent such networks is a multi-agent system (MAS), where independent software modules (agents) encapsulate properties and functionalities. agentMET4FOF is an interactive and flexible open-source implementation of such a MAS. The software engineering process is driven by several industry-oriented use cases with the aim of impacting on IIoT applications. This leads to a framework that is specialized in representing heterogeneous sensor networks.

A special emphasize is put on supporting metrological treatment of sensor streaming data. This includes the consideration of measurement uncertainties during data analysis and processing as well as propagating metadata alongside the data itself.

One of the many questions that drive us in the project is:

How can metrological input be incorporated into an agent-based system for addressing uncertainty of machine learning in future manufacturing?

📈The agentMET4FOF dashboard

agentMET4FOF comes bundled with our so called dashboard. It is an optional component of every agent network and provides a web browser based view. You can observe the state of your agents, modify the connections between them and even add more pre-made agents to your network all during run-time. The address to your dashboard is printed to the console on every launch of an agent network.

The following image is close to what you will find in your browser on execution of tutorial 2. For details on the tutorials visit our video tutorial series.

Web Screenshot

📖Documentation and video tutorials

Extended documentation can be found on ReadTheDocs.

Video tutorial series

Additionally, we provide some video tutorials based on agentMET4FOF 0.4.1 on the project homepage in the section Tutorials for the multi-agent system agentMET4FOF. You can self-register on the linked page and get started immediately. The video series begins with our motivation for creating agentMET4FOF, guide you through the installation of Python and other recommended software until you execute the tutorials on your machine.

Live online tutorial during early development

In an early development stage we held a live online tutorial based on agentMET4FOF 0.1.0 which you can download.

If questions arise, or you feel something is missing, reach out to us.

💻Installation

The installation of agentMET4FOF is as straightforward as the Python ecosystem suggests. In the video tutorials series we guide you through every step until you have agentMET4FOF running on your machine. Besides that we have more details in the installation section of the docs.

💨Coming soon

  • Dockerize agentMET4FOF
  • Improve handling of metadata
  • Further improve plotting

For a comprehensive overview of current development activities and upcoming tasks, take a look at the project board, issues and pull requests.

🖋Citation

If you publish results obtained with the help of agentMET4FOF, please cite the linked DOI.

💎Acknowledgement

This work was part of the Joint Research Project Metrology for the Factory of the Future (Met4FoF), project number 17IND12 of the European Metrology Programme for Innovation and Research (EMPIR). The EMPIR is jointly funded by the EMPIR participating countries within EURAMET and the European Union.

⚠Disclaimer

This software is developed as a joint effort of several project partners namely:

under the lead of IfM. The software is made available "as is" free of cost. The authors and their institutions assume no responsibility whatsoever for its use by other parties, and makes no guarantees, expressed or implied, about its quality, reliability, safety, suitability or any other characteristic. In no event will the authors be liable for any direct, indirect or consequential damage arising in connection with the use of this software.

©License

agentMET4FOF is distributed under the LGPLv3 license.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

agentMET4FOF-0.6.1.tar.gz (1.7 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

agentMET4FOF-0.6.1-py3-none-any.whl (48.6 kB view details)

Uploaded Python 3

File details

Details for the file agentMET4FOF-0.6.1.tar.gz.

File metadata

  • Download URL: agentMET4FOF-0.6.1.tar.gz
  • Upload date:
  • Size: 1.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.57.0 CPython/3.8.8

File hashes

Hashes for agentMET4FOF-0.6.1.tar.gz
Algorithm Hash digest
SHA256 6b8172145f356d5ae42fd144d0be0dd025169b861f6c6eb266d4363ae96c4a34
MD5 763d3ff9299de05d766e91f42a73980b
BLAKE2b-256 e75fdc73c76442b7f337dc5e5165b063eba35fceb9089e92886bedad800cf353

See more details on using hashes here.

File details

Details for the file agentMET4FOF-0.6.1-py3-none-any.whl.

File metadata

  • Download URL: agentMET4FOF-0.6.1-py3-none-any.whl
  • Upload date:
  • Size: 48.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/49.2.1 requests-toolbelt/0.9.1 tqdm/4.57.0 CPython/3.8.8

File hashes

Hashes for agentMET4FOF-0.6.1-py3-none-any.whl
Algorithm Hash digest
SHA256 08b3e719c79f40e2e5be1b1ab4347c1f73bc4dcbf87ac52bf04384cd71577f4e
MD5 ea2112e6c8064835cf04888848884f33
BLAKE2b-256 82ebe0a79ccf3f509a67be13a712457aeb8fc80f83b31f50fd638a74a9b7c516

See more details on using hashes here.

Release history Release notifications | RSS feed

0.13.4

2 files

0.13.3

2 files

0.13.2

2 files

0.13.1

2 files

0.13.0

2 files

0.12.1

2 files

0.12.0

2 files

0.11.0

2 files

0.10.1

2 files

0.10.0

2 files

0.9.0

2 files

0.8.1

2 files

0.8.0

2 files

0.7.0

2 files

0.6.4

2 files

0.6.3

2 files

0.6.2

2 files

This release

0.6.1 This release

2 files

0.6.0

2 files

0.5.2

2 files

0.5.1

2 files

0.5.0

2 files

0.4.1

2 files

0.4.0

2 files

0.3.0

2 files

0.2.2

2 files

0.2.1

2 files

0.2.0

2 files

0.1.11

2 files

0.1.10

2 files

0.1.9

2 files

0.1.8

2 files

0.1.7

2 files

0.1.6

2 files

0.1.5

2 files

0.1.4

2 files

0.1.3

2 files

0.1.2

2 files

0.1.1

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page