Control your heat-pump/aircondition and screens to maintain a optimal indoor temperature based on outdoor and indoor temperature sensors
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Updated
Nov 28, 2024 - Python
Control your heat-pump/aircondition and screens to maintain a optimal indoor temperature based on outdoor and indoor temperature sensors
business plan for a self-sustaining smart farm/data-center
OpenTherm gateway for HomeAssistant
Es handelt sich um ein Modul für FHEM, um Klimageräte von Daikin über die Daikin-Cloud zu steuern.
Python client for Unisenza Plus
Hydronics Control System and Smart Thermostat, IoT
A silly simulation to try and mimic real life HVAC problems to solve.
ESPHome component for AUX based air conditioners. Direct wifi control of HVAC by ESPHome and Home Assistant. HVAC status and command feedback are available.
This is a framework for Automated Supervisory Optimization (ASO) with built-in BACnet methods.
Enhancing HVAC Control Efficiency: A Hybrid Approach Using Imitation and Reinforcement Learning
A novel method to incorporate existing policy (Rule-based control) with Reinforcement Learning.
Infrared remote library for ESP8266/ESP32: send and receive infrared signals with multiple protocols. Based on: https://github.com/shirriff/Arduino-IRremote/
App to scrape bacnet system inside building continuously, compile a CSV file, and code to run on a different machine to SCP the CSV files across a VPN to a project SharePoint drive
HVACGraphicsClassifier is an experimental tinyML project aimed at classifying HVAC control system graphics using computer vision. A project goal from the start is support of Tiny ML Micro, allowing models to be quantized to run on microcontrollers with the TensorFlow C library.
Open source heat pump controller and home automation terminal, built on ESP32
Open home assistant integration for CoolAutomation cloud API
Turkov integration for Home Assistant
Lessmostat, the less is more esp8266 WIFI AC thermostat: less than $25 in amazon pieces, no soldering, no breadboarding, no need for AC C wire.
Enhancing HVAC Control Systems through Transfer Learning with Deep Reinforcement Learning Agents
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