🏠 Unified environmental sensing and smart home integration framework - enabling AI assistants to perceive the physical world
Homeware Sense is a unified environmental sensing skill that allows the OpenClaw AI assistant to perceive and respond to physical environment changes. This skill supports multiple smart home platforms including HomeKit, Mi Home, MQTT, GPIO, and simulators.
- Apple HomeKit: Native support for HomeKit compatible devices
- Xiaomi Mi Home: Integration with Xiaomi ecosystem devices
- MQTT Protocol: Support for generic MQTT sensors
- GPIO Interface: Support for Raspberry Pi GPIO sensors
- Smart Simulation: Develop and test without hardware
- Unified API: Same interface for all platforms
- Auto Discovery: Automatically detect available hardware platforms
- Fallback: Automatically switch to simulator when hardware is unavailable
- Minimal Code: Integrate platforms with just a few lines of code
- Real-time Monitoring: Temperature, humidity, light, sound, motion, air quality
- Smart Alerts: Automatic notifications when thresholds are exceeded
- Data Aggregation: Analyze data from multiple sensors
cd ~/.openclaw/skills/
git clone https://github.com/jiawei686/homeware-sense-skill.gitcd ~/.openclaw/skills/
curl -L https://github.com/jiawei686/homeware-sense-skill/archive/main.zip -o homeware-sense-skill.zip
unzip homeware-sense-skill.zip
mv homeware-sense-skill-main homeware-sense-skillfrom homeware_sense_skill import HomewareSenseSkill
# Auto-connect to all available platforms
skill = HomewareSenseSkill.quick_connect('auto')
data = skill.get_environment_data()
print(data)from homeware_sense_skill import HomewareSenseSkill
# Connect to specific platform
skill = HomewareSenseSkill.quick_connect('homekit') # HomeKit
skill = HomewareSenseSkill.quick_connect('mihome') # Mi Home
skill = HomewareSenseSkill.quick_connect('mqtt') # MQTT
skill = HomewareSenseSkill.quick_connect('gpio') # GPIOfrom homeware_sense_skill import HomewareSenseSkill
# Custom configuration
config = {
'debug': True,
'sensors_enabled': {
'temperature': True,
'humidity': True,
'light': True
},
'hardware_config': {
'temperature': {
'enabled': True,
'type': 'homekit', # or 'mihome', 'mqtt', 'gpio', 'mock'
'accessory_id': 'com.example.sensor',
'pin_code': '123-45-678',
'sensor_type': 'temperature',
'location': 'living_room'
}
}
}
skill = HomewareSenseSkill(config)
data = skill.get_environment_data()| Sensor Type | Description | Unit |
|---|---|---|
| temperature | Temperature | °C |
| humidity | Humidity | % |
| light | Light intensity | lux |
| sound | Sound level | dB |
| motion | Motion detection | boolean |
| air_quality | Air quality | AQI |
Get current environment data
result = skill.get_environment_data()
# Returns: {
# 'success': bool,
# 'data': {...},
# 'error': str | None,
# 'meta': {...}
# }Set sensor thresholds
thresholds = {
'temperature': [18, 26], # [min, max]
'humidity': [30, 70]
}
result = skill.set_thresholds(thresholds)Get platform connection status
status = skill.get_platform_status()Quickly connect to specified platform
skill = HomewareSenseSkill.quick_connect('auto')debug: Enable debug modesensors_enabled: Control enabled sensor typespolling_interval: Data polling interval (seconds)data_retention_days: Data retention days
{
"hardware_config": {
"temperature": {
"enabled": true,
"type": "homekit",
"accessory_id": "com.example.temperature-sensor",
"pin_code": "123-45-678",
"sensor_type": "temperature",
"location": "living_room"
}
}
}{
"hardware_config": {
"humidity": {
"enabled": true,
"type": "mihome",
"device_ip": "192.168.1.100",
"device_token": "your_mihome_device_token",
"sensor_type": "air_monitor",
"location": "bedroom"
}
}
}{
"hardware_config": {
"light": {
"enabled": true,
"type": "mqtt",
"host": "localhost",
"port": 1883,
"topic": "sensors/light",
"location": "kitchen"
}
}
}Depending on the hardware platform used, additional dependencies may be required:
# HomeKit Support
pip install HAP-python
# Mi Home Support
pip install python-miio
# MQTT Support
pip install paho-mqtt
# Flask for API interface (optional)
pip install flaskfrom homeware_sense_skill import HomewareSenseSkill
skill = HomewareSenseSkill.quick_connect('auto')
data = skill.get_environment_data()
temp = data['data']['environment_status']['temperature']
if temp > 26:
print("Temperature too high, suggest turning on AC")
elif temp < 18:
print("Temperature too low, suggest turning on heater")from homeware_sense_skill import HomewareSenseSkill
skill = HomewareSenseSkill.quick_connect('auto')
data = skill.get_environment_data()
light = data['data']['environment_status']['light_level']
if light < 100: # Dark environment
print("Suggest turning on indoor lighting")from homeware_sense_skill import HomewareSenseSkill
skill = HomewareSenseSkill.quick_connect('auto')
thresholds = {
'temperature': [15, 30],
'humidity': [30, 70],
'air_quality': [0, 100]
}
skill.set_thresholds(thresholds)
data = skill.get_environment_data()
alerts = data['data']['alerts']
if alerts:
for alert in alerts:
print(f"Alert: {alert['message']}")Issues and Pull Requests are welcome to improve the Homeware Sense skill!
# Clone the repository
git clone https://github.com/jiawei686/homeware-sense-skill.git
cd homeware-sense-skill
# Create virtual environment
python -m venv venv
source venv/bin/activate # Linux/Mac
# or venv\Scripts\activate # Windows
# Install development dependencies
pip install -e .python -m unittest discover -s ./test_homeware_sense_skill.pyMIT License - See LICENSE file for details
Thanks to the OpenClaw community for support and feedback.
⭐ If this project helps you, please give it a Star!