HA integration for CH/DHW and HVAC systems that use the RAMSES II RF protocol
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Updated
Jun 26, 2024 - Python
Robot Framework is an open source, easy to learn, and easy to use, yet powerful, and extendable, generic automation framework for software testing and RPA (robotic process automation). While it's original purpose was to support acceptance testing and acceptance test driven development
(ATDD) of embedded software at Nokia Networks back in 2005, nowadays it is also widely used for automation of integration tests
and end-to-end tests
in desktop, web, and mobile development. You can use it to automate GUI based applications as well as REST, RPC, SOAP and other API, and protocol based testing. Due to it's text based nature and cli tools RF is a perfect match for agile and DevOps, and DevSecOps driven projects striving to succeed in continuous testing. It integrates very well with open source and commercial CI/CD solutions like Jenkins, CircleCI, GitHub Actions, and Azure Pipelines - just to name a few. It is also developer friendly and can easily be versioned with Git, and used with Docker and other container and virtualisation technologies to support building and maintaining of scalable (test) environments following the configuration as code
or infrastructure as code
approach. RF can be used in projects of any technology stack, and runs on any infrastructure (Windows, Mac, Linux, cloud) - it is stack and infrastructure agnostic.
HA integration for CH/DHW and HVAC systems that use the RAMSES II RF protocol
PySDR.org textbook source material, feel free to post issues/PRs
A web-based SDR toolkit for analyzing, processing, and sharing RF recordings
RF/Microwave simulations and projects
Python module for instrument control and automation.
System to capture digital signaldata and transfer them to another system
Example for Node IoT use RAK3172
The board contains an STM32 microcontroller, an RF transceiver and antenna interface as well as a USB full-speed interface
Course materials supporting NTIA/ITS's ISART 2024 Tutorial on building and evaluating statistical propagation model. Focused on clutter modeling.
Notes and simulations on modulations at the waveform level
Created by Pekka Klärck
Released 06 2008
Latest release 16 days ago