motion detection example home assistant

examples/motion_detector.py

@@ -3,7 +3,6 @@ This example shows how to use the CSI framework to connect to a FeitCSI host and
 detect changes in the environment
 """
 
-import logging
 from queue import Queue
 
 import numpy as np
@@ -16,37 +15,46 @@ from where_fi.collection.ingest import RealtimeCSIProducer
 producer = RealtimeCSIProducer()
 app = CSIApplication(producer)
 
-# Store historical CSI data to compare with the current data
-# This allows us to detect sudden changes in the environment,
-# most likely to be cause by motion
 
-# This is stored individually for each receiving antenna, for each subcarrier
+# Stores historical data for each receiving antenna, for each subcarrier
 historical: dict[tuple[int, int], Queue[np.complex64]] = {}
 
 MAGN_THRESHOLD = 20
 PHASE_THRESHOLD = 0.5
+QUEUE_SIZE = 2000
 
 
 @app.on_process
-def _(antenna_data: npt.NDArray[np.complex64]) -> None:
-    for antenna in range(antenna_data.shape[1]):
-        for subcarrier in range(antenna_data.shape[0]):
+def _(sample: npt.NDArray[np.complex64]) -> None:
+    """
+    Process the CSI data and detect changes in the environment.
+
+    This function is called by the framework at a fixed interval, with the latest CSI
+    sample received.
+
+    It is used to detect changes in the environment caused by motion, by comparing each
+    entry in the matrix with a moving average
+    """
+    change = False
+    for antenna in range(sample.shape[1]):
+        for subcarrier in range(sample.shape[0]):
             # Get the current subcarrier data
-            current = antenna_data[subcarrier, antenna, 0]
+            current = sample[subcarrier, antenna, 0]
 
             # Get the historical data for this antenna and subcarrier
             if (antenna, subcarrier) not in historical:
-                historical[(antenna, subcarrier)] = Queue(maxsize=100)
+                historical[(antenna, subcarrier)] = Queue(maxsize=QUEUE_SIZE)
             historical_data = historical[(antenna, subcarrier)]
 
-            # Calculate the average of the historical data
-            mean: np.complex64 = np.mean(historical_data.queue)
+            # Calculate the average of the historical data for this antenna and
+            # subcarrier
+            mean = np.mean(historical_data.queue)
 
             # If we have enough historical data, compare it with the current data
             if historical_data.full():
                 historical_data.get()
 
-            # Add the current data to the historical data
+            # Add the current sample to the historical data
             historical_data.put(current)
 
             # Compare the current data with the historical data
@@ -54,11 +62,11 @@ def _(antenna_data: npt.NDArray[np.complex64]) -> None:
                 np.abs(mean - current) > MAGN_THRESHOLD
                 or np.abs(np.angle(mean) - np.angle(current)) > PHASE_THRESHOLD
             ):
-                logging.info(
-                    f"Change detected on antenna {antenna}, subcarrier {subcarrier} "
-                    f"|{np.abs(mean - current)}| <{np.angle(mean) - np.angle(current)}>"
-                )
+                change = True
+    if change:
+        print("Motion detected!")
+    else:
+        print("No motion detected!")
 
 
-# Start the application
 app.start()

examples/motion_detector_home_assistant.py

@@ -0,0 +1,109 @@
+"""Motion Detection example
+This example shows how to use the CSI framework to connect to a FeitCSI host and
+detect changes in the environment
+
+Once motion is detected, the application will log the change to Home Assistant
+through an HTTP request.
+"""
+
+import os
+from queue import Queue
+
+import numpy as np
+import numpy.typing as npt
+import requests
+
+from where_fi.application import CSIApplication
+from where_fi.collection.ingest import RealtimeCSIProducer
+
+# Connect to a FeitCSI host
+producer = RealtimeCSIProducer()
+app = CSIApplication(producer)
+
+
+class HomeAssistantBinarySensor:
+    """
+    Represents a binary sensor in Home Assistant.
+
+    Uses the HTTP API [1] to update the state of the sensor.
+
+    [1] - https://www.home-assistant.io/integrations/http/#binary-sensor
+    """
+
+    def __init__(self, id: str, name: str) -> None:
+        self.id = id
+        self.name = name
+
+        BASE_URL = os.getenv("HOME_ASSISTANT_URL")
+        API_KEY = os.getenv("HOME_ASSISTANT_API_KEY")
+
+        self.url = f"{BASE_URL}/api/states/binary_sensor.{self.id}"
+        self.headers = {"Authorization": f"Bearer {API_KEY}"}
+
+        self.state = False
+
+    def update(self, state: bool) -> None:
+        if self.state == state:
+            return
+
+        self.state = state
+        data = {
+            "state": "on" if state else "off",
+            "attributes": {"friendly_name": self.name},
+        }
+        requests.post(self.url, json=data, headers=self.headers)
+
+
+# Stores historical data for each receiving antenna, for each subcarrier
+historical: dict[tuple[int, int], Queue[np.complex64]] = {}
+sensor = HomeAssistantBinarySensor("motion_detector", "Motion Detector")
+
+MAGN_THRESHOLD = 20
+PHASE_THRESHOLD = 0.5
+QUEUE_SIZE = 2000
+
+
+@app.on_process
+def _(sample: npt.NDArray[np.complex64]) -> None:
+    """
+    Process the CSI data and detect changes in the environment.
+
+    This function is called by the framework at a fixed interval, with the latest CSI
+    sample received.
+
+    It is used to detect changes in the environment caused by motion, by comparing each
+    entry in the matrix with a moving average
+    """
+    change = False
+    for antenna in range(sample.shape[1]):
+        for subcarrier in range(sample.shape[0]):
+            # Get the current subcarrier data
+            current = sample[subcarrier, antenna, 0]
+
+            # Get the historical data for this antenna and subcarrier
+            if (antenna, subcarrier) not in historical:
+                historical[(antenna, subcarrier)] = Queue(maxsize=QUEUE_SIZE)
+            historical_data = historical[(antenna, subcarrier)]
+
+            # Calculate the average of the historical data for this antenna and
+            # subcarrier
+            mean = np.mean(historical_data.queue)
+
+            # If we have enough historical data, compare it with the current data
+            if historical_data.full():
+                historical_data.get()
+
+            # Add the current sample to the historical data
+            historical_data.put(current)
+
+            # Compare the current data with the historical data
+            if (
+                np.abs(mean - current) > MAGN_THRESHOLD
+                or np.abs(np.angle(mean) - np.angle(current)) > PHASE_THRESHOLD
+            ):
+                change = True
+
+    sensor.update(change)
+
+
+app.start()

pyproject.toml

@@ -15,6 +15,7 @@ dependencies = [
     "pydantic>=2.10.6",
     "torch",
     "grpcio>=1.70.0",
+    "requests>=2.32.3",
 ]
 
 [build-system]
@@ -54,4 +55,5 @@ dev = [
     "grpcio-tools>=1.70.0",
     "matplotlib-stubs>=0.1.0",
     "protoletariat>=3.3.9",
+    "types-requests>=2.32.0.20250328",
 ]