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Add temperature compensation and webcam mic noise sensing

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- Temperature: dynamic compensation using CPU temp (factor=1.85, calibrated for eye1)
- Noise: uses arecord from webcam mic instead of broken MEMS HAT mic
- Config: added sensors section for temp_factor and noise_device
- API: now returns raw_temp and cpu_temp alongside compensated temp

Calibration: 69°F actual ambient
🦊 Christmas Eve 2025
This commit is contained in:
Alex Kazaiev
2025-12-24 12:38:49 -06:00
parent 524c37a8c4
commit baf7e417c1
3 changed files with 184 additions and 41 deletions
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12
config.example.yaml
View File

@@ -11,6 +11,18 @@ database:
sampling:
interval_seconds: 60 # How often to read sensors
sensors:
# Temperature compensation factor for CPU heat bleed
# Calibrate by comparing raw sensor temp to actual ambient
# factor = (cpu_temp - raw_temp) / (raw_temp - actual_temp)
# eye1.local calibration: CPU=49.4°C, Raw=30.7°C, Actual=20.6°C → factor=1.85
temp_compensation_factor: 1.85
# ALSA device for noise sensing (webcam mic)
# Use "default" for system default, or specify like "hw:1,0"
# Run "arecord -l" to list available devices
noise_device: "default"
lcd:
enabled: true
brightness: 0.5

8
main.py
View File

@@ -46,6 +46,7 @@ def load_config(config_path: str = "config.yaml") -> dict:
"server": {"host": "0.0.0.0", "port": 8767},
"database": {"path": "enviro_history.db", "retention_hours": 168},
"sampling": {"interval_seconds": 60},
"sensors": {"temp_compensation_factor": 1.85, "noise_device": "default"},
"lcd": {"enabled": True, "brightness": 0.5, "default_message": "🦊 Vixy"},
"mock_mode": False
}
@@ -154,7 +155,12 @@ async def lifespan(app: FastAPI):
mock_mode = config.get("mock_mode", False)
# Initialize components
sensors = get_sensors(mock_mode=mock_mode)
sensor_config = config.get("sensors", {})
sensors = get_sensors(
mock_mode=mock_mode,
temp_factor=sensor_config.get("temp_compensation_factor", 1.85),
noise_device=sensor_config.get("noise_device", "default")
)
db = await get_database(
db_path=config["database"]["path"],
retention_hours=config["database"]["retention_hours"]

203
sensors.py
View File

@@ -2,19 +2,26 @@
Sensor reading module for Pimoroni Enviro Mini HAT.
Provides unified interface to:
- BME280: Temperature, Humidity, Pressure
- BME280: Temperature, Humidity, Pressure (with CPU heat compensation)
- LTR559: Light level, Proximity
- MEMS Microphone: Noise level
- Webcam Microphone: Noise level via arecord
"""
import time
import logging
import subprocess
import struct
from dataclasses import dataclass
from typing import Optional
from typing import Optional, Tuple
import numpy as np
logger = logging.getLogger(__name__)
# Temperature compensation factor - calibrated for eye1.local
# factor = (cpu_temp - raw_temp) / (raw_temp - actual_temp)
# Calibrated: CPU=49.4°C, Raw=30.7°C, Actual=20.6°C (69°F) → factor=1.85
TEMP_COMPENSATION_FACTOR = 1.85
# Sensor imports - will fail gracefully if not on Pi
try:
from bme280 import BME280
@@ -31,12 +38,106 @@ except ImportError:
LTR559_AVAILABLE = False
logger.warning("LTR559 library not available - using mock data")
def get_cpu_temperature() -> float:
"""
Read CPU temperature from system.
Returns:
CPU temperature in Celsius, or 0.0 if unavailable
"""
try:
import sounddevice as sd
SOUNDDEVICE_AVAILABLE = True
except ImportError:
SOUNDDEVICE_AVAILABLE = False
logger.warning("sounddevice not available - using mock data")
# Try vcgencmd first (Raspberry Pi specific)
result = subprocess.run(
['vcgencmd', 'measure_temp'],
capture_output=True,
text=True,
timeout=2
)
if result.returncode == 0:
# Parse "temp=49.4'C"
temp_str = result.stdout.strip()
temp = float(temp_str.replace("temp=", "").replace("'C", ""))
return temp
except (subprocess.TimeoutExpired, FileNotFoundError, ValueError):
pass
try:
# Fallback: read from thermal zone
with open('/sys/class/thermal/thermal_zone0/temp', 'r') as f:
temp = float(f.read().strip()) / 1000.0
return temp
except (FileNotFoundError, ValueError):
pass
logger.warning("Could not read CPU temperature")
return 0.0
def read_noise_from_mic(device: str = "default", duration: float = 0.5) -> float:
"""
Read noise level from webcam/USB microphone using arecord.
Args:
device: ALSA device name (default uses system default)
duration: How long to sample in seconds
Returns:
RMS noise level (0-100 scale)
"""
try:
# Use arecord to capture raw audio
# Format: signed 16-bit little-endian, mono, 16kHz
result = subprocess.run(
[
'arecord',
'-D', device,
'-f', 'S16_LE',
'-c', '1',
'-r', '16000',
'-d', str(int(duration + 0.5)), # duration in seconds (rounded up)
'-t', 'raw',
'-q', # quiet
'-' # output to stdout
],
capture_output=True,
timeout=duration + 2
)
if result.returncode != 0:
logger.warning(f"arecord failed: {result.stderr.decode()}")
return 0.0
# Parse raw audio data
raw_data = result.stdout
if len(raw_data) < 2:
return 0.0
# Convert to numpy array of int16
samples = np.frombuffer(raw_data, dtype=np.int16)
if len(samples) == 0:
return 0.0
# Calculate RMS
rms = np.sqrt(np.mean(samples.astype(np.float64)**2))
# Normalize to 0-100 scale
# int16 max is 32767, so RMS of full-scale would be ~23170
# Scale so moderate noise (~5000 RMS) is around 50
noise_level = min(100, (rms / 5000) * 50)
return noise_level
except subprocess.TimeoutExpired:
logger.warning("arecord timed out")
return 0.0
except FileNotFoundError:
logger.warning("arecord not found - noise sensing disabled")
return 0.0
except Exception as e:
logger.error(f"Error reading noise level: {e}")
return 0.0
@dataclass
@@ -45,6 +146,8 @@ class EnviroReading:
timestamp: float
temperature_c: float
temperature_f: float
temperature_raw_c: float # Before compensation
cpu_temp_c: float
humidity: float
pressure: float
light: float
@@ -56,6 +159,8 @@ class EnviroReading:
"timestamp": self.timestamp,
"temperature_c": round(self.temperature_c, 1),
"temperature_f": round(self.temperature_f, 1),
"temperature_raw_c": round(self.temperature_raw_c, 1),
"cpu_temp_c": round(self.cpu_temp_c, 1),
"humidity": round(self.humidity, 1),
"pressure": round(self.pressure, 1),
"light": round(self.light, 1),
@@ -67,14 +172,23 @@ class EnviroReading:
class EnviroSensors:
"""Interface to Enviro Mini HAT sensors."""
def __init__(self, mock_mode: bool = False):
def __init__(
self,
mock_mode: bool = False,
temp_factor: float = TEMP_COMPENSATION_FACTOR,
noise_device: str = "default"
):
"""
Initialize sensors.
Args:
mock_mode: If True, return fake data (for testing without hardware)
temp_factor: Temperature compensation factor
noise_device: ALSA device for noise sensing
"""
self.mock_mode = mock_mode or not (BME280_AVAILABLE and LTR559_AVAILABLE)
self.temp_factor = temp_factor
self.noise_device = noise_device
if not self.mock_mode:
try:
@@ -93,15 +207,32 @@ class EnviroSensors:
if self.mock_mode:
logger.info("Running in mock mode")
def read_temperature(self) -> tuple[float, float]:
"""Read temperature in Celsius and Fahrenheit."""
if self.mock_mode:
temp_c = 20.0 + np.random.uniform(-2, 2)
else:
temp_c = self.bme280.get_temperature()
def read_temperature(self, compensate: bool = True) -> Tuple[float, float, float, float]:
"""
Read temperature in Celsius and Fahrenheit with CPU heat compensation.
temp_f = (temp_c * 9/5) + 32
return temp_c, temp_f
Args:
compensate: Apply CPU heat compensation
Returns:
Tuple of (compensated_c, compensated_f, raw_c, cpu_c)
"""
if self.mock_mode:
raw_c = 20.0 + np.random.uniform(-2, 2)
cpu_c = 45.0 + np.random.uniform(-5, 5)
else:
raw_c = self.bme280.get_temperature()
cpu_c = get_cpu_temperature()
# Apply compensation: temp = raw - ((cpu - raw) / factor)
if compensate and cpu_c > 0 and self.temp_factor > 0:
compensated_c = raw_c - ((cpu_c - raw_c) / self.temp_factor)
else:
compensated_c = raw_c
compensated_f = (compensated_c * 9/5) + 32
return compensated_c, compensated_f, raw_c, cpu_c
def read_humidity(self) -> float:
"""Read relative humidity percentage."""
@@ -129,7 +260,7 @@ class EnviroSensors:
def read_noise(self, duration: float = 0.5) -> float:
"""
Read noise level from microphone.
Read noise level from webcam microphone.
Args:
duration: How long to sample in seconds
@@ -137,35 +268,21 @@ class EnviroSensors:
Returns:
RMS noise level (0-100 scale)
"""
if self.mock_mode or not SOUNDDEVICE_AVAILABLE:
if self.mock_mode:
return np.random.uniform(20, 40)
try:
# Record audio sample
sample_rate = 16000
samples = int(duration * sample_rate)
recording = sd.rec(samples, samplerate=sample_rate, channels=1, dtype='float32')
sd.wait()
# Calculate RMS
rms = np.sqrt(np.mean(recording**2))
# Convert to 0-100 scale (rough approximation)
noise_level = min(100, rms * 1000)
return noise_level
except Exception as e:
logger.error(f"Error reading noise level: {e}")
return 0.0
return read_noise_from_mic(device=self.noise_device, duration=duration)
def read_all(self) -> EnviroReading:
"""Get a complete reading from all sensors."""
temp_c, temp_f = self.read_temperature()
temp_c, temp_f, raw_c, cpu_c = self.read_temperature()
return EnviroReading(
timestamp=time.time(),
temperature_c=temp_c,
temperature_f=temp_f,
temperature_raw_c=raw_c,
cpu_temp_c=cpu_c,
humidity=self.read_humidity(),
pressure=self.read_pressure(),
light=self.read_light(),
@@ -177,9 +294,17 @@ class EnviroSensors:
# Singleton instance
_sensors: Optional[EnviroSensors] = None
def get_sensors(mock_mode: bool = False) -> EnviroSensors:
def get_sensors(
mock_mode: bool = False,
temp_factor: float = TEMP_COMPENSATION_FACTOR,
noise_device: str = "default"
) -> EnviroSensors:
"""Get or create the sensors instance."""
global _sensors
if _sensors is None:
_sensors = EnviroSensors(mock_mode=mock_mode)
_sensors = EnviroSensors(
mock_mode=mock_mode,
temp_factor=temp_factor,
noise_device=noise_device
)
return _sensors