Bt monitor

.gitignore

@@ -5,4 +5,4 @@ ve_*
 /music
 __pycache__
 /roles/pi-squeezeserver/backup
-venv
+venv*

.vscode/settings.json

@@ -1,5 +1,8 @@
 {
     "python.linting.pylintEnabled": false,
     "python.linting.enabled": true,
-    "python.linting.flake8Enabled": true
+    "python.linting.flake8Enabled": true,
+    "files.associations": {
+        "*.yaml": "home-assistant"
+    }
 }

full.yml

@@ -41,13 +41,21 @@
     - pi-disable-onboard-bluetooth
     - bluetooth-monitor
 
+- hosts: musicmouse
+  roles:
+    - pi-standard-setup
+    - pi-hifiberry-amp
+    - pi-musicmouse
+    - pi-squeezelite-custom
+    - pi-shairport
+    - pi-lirc
+    - bluetooth-monitor
+
 #- hosts: octopi
 #  roles:
 #    - pi-dhtsensor
     
-
 #- hosts: newrpi
 #  roles:
 #     - pi-standard-setup
 #     - pi-lirc
-

inventory.yml

@@ -12,12 +12,16 @@ all:
           sensor_room_name_ascii: prusaprinter
           sensor_room_name: prusaprinter
           dht_pin: 26
+          main_user: root
         bedroompi:
           squeezelite_name: BedroomPi
           shairport_name: BedroomPi
           alsa_card_name: Codec
           sensor_room_name_ascii: schlafzimmer
           sensor_room_name: Schlafzimmer
+          my_bt_monitor_watchdog_seconds: 600
+          my_btmonitor_restart_ble_interface: hci0
+          main_user: root
         kitchenpi:
           squeezelite_name: KitchenPi
           shairport_name: KitchenPi
@@ -25,6 +29,7 @@ all:
           sensor_room_name_ascii: kueche
           sensor_room_name: Küche
           hifiberry_overlay: hifiberry-amp
+          main_user: root
         esszimmerradio: # oben, eltern
           squeezelite_name: Esszimmer
           shairport_name: _Oben_Esszimmer
@@ -32,6 +37,7 @@ all:
           squeezeserver: 192.168.178.100
           configure_wifi: true
           alsa_card_name: 1
+          main_user: root
         musikserverwohnzimmeroben: # oben, eltern
           squeezelite_name: Wohnzimmer
           shairport_name: _Oben_Wohnzimmer
@@ -40,12 +46,15 @@ all:
           sensor_room_name_ascii: wohnzimmeroben
           sensor_room_name: WohnzimmerOben
           hifiberry_overlay: hifiberry-dacplus
-          my_btmonitor_pl0: 68 # default is 73 - increase to make more sensitve (i.e. lower distances)
+          main_user: root
         musicmouse:
           squeezelite_name: MusicMouse
           shairport_name: MusicMouse
-          alsa_card_name: 0
+          alsa_card_name: 1
           hifiberry_overlay: hifiberry-dacplus
+          sensor_room_name: Kinderzimmer
+          sensor_room_name_ascii: kinderzimmer
+          main_user: root
         newrpi:
           squeezelite_name: MyTestRaspberry
           shairport_name: MyTestRaspberry
@@ -56,7 +65,12 @@ all:
         server:
           sensor_room_name: Arbeitszimmer
           sensor_room_name_ascii: arbeitszimmer
-          my_btmonitor_pl0: 78
+          my_bt_monitor_watchdog_seconds: 600
+          my_btmonitor_restart_ble_interface: hci0
+          main_user: core
+        homeassistant:
+          sensor_room_name: Anschlussraum
+          sensor_room_name_ascii: anschlussraum
   vars:
     ansible_user: root
     ansible_python_interpreter: /usr/bin/python3

roles/better-shell-env/tasks/files/dot.fish

@@ -0,0 +1,3 @@
+function dot -w git -d "Manages dotfiles"
+    git --git-dir=$HOME/.dot --work-tree=$HOME $argv
+end

roles/better-shell-env/tasks/main.yml

@@ -0,0 +1,47 @@
+---
+# 
+- name: Install packages
+  apt:
+    name:
+      - bat
+      - broot
+      - duf
+      - fd-find
+      - fish
+      - fzf
+      - git
+      - glances
+      - lsd
+      - neovim
+      - ripgrep
+      - tmux
+      - zoxide
+
+# TODO: Dust, btm
+
+block:
+  become: true
+  become_user: {{main_user}}
+  - name: Create bin folder
+    ansible.builtin.file:
+      path: ~/bin
+      state: directory
+      mode: '0755'
+
+  # Oh-my-fish
+  - name: get oh-my-fish repo
+    git:
+      repo: 'https://github.com/oh-my-fish/oh-my-fish.git'
+      dest: ~/.local/share/git/oh-my-fish
+  - name: install oh-my-fish
+    shell:
+      cmd: "bin/install --offline --noninteractive"
+      executable: /usr/bin/fish
+      chdir: ~/.local/share/git/oh-my-fish
+    creates:
+      - ~/.local/share/omf
+      - ~/.config/omf
+  - copy:
+      content: "bobthefish"
+      dst: "~/.config/omf/theme"
+

roles/bluetooth-monitor/other/Dockerfile

@@ -0,0 +1,11 @@
+FROM python:3
+
+WORKDIR /usr/src/app
+
+COPY requirements.txt ./
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY bt_monitor_server.py .
+COPY training_data.csv .
+
+CMD [ "python", "./bt_monitor_server.py" ]

roles/bluetooth-monitor/other/analysis.py

@@ -0,0 +1,95 @@
+from pathlib import Path
+import pandas as pd
+import numpy as np
+from copy import copy
+from sklearn.model_selection import cross_val_score
+from sklearn import svm
+from sklearn.neural_network import MLPClassifier
+from sklearn.metrics import confusion_matrix, ConfusionMatrixDisplay
+import matplotlib.pyplot as plt
+from sklearn.model_selection import train_test_split
+
+def load_measurements(csv_file: Path):
+  def cleanup_column_name(col_name: str):
+    clean_name = col_name.replace('#', '').strip()
+    if clean_name == 'room':
+      return 'tracker'
+    return clean_name
+
+  df = pd.read_csv(str(csv_file))
+
+  # String cleanup in column names and room names
+  df = df.rename(columns=cleanup_column_name)
+  df.applymap(lambda x: x.strip() if isinstance(x, str) else x)
+
+  df['tracker'] = df['tracker'].astype("category")
+  df['real_room'] = df['real_room'].astype("category")
+
+  return df
+
+
+FAR_AWAY_FEATURE_VALUE = 1
+def get_feature_value(rssi, tx_power):
+  MIN_RSSI = -90
+  MAX_TRANSFORMED_RSSI = 40
+  v = tx_power - rssi - MAX_TRANSFORMED_RSSI
+  if v < 0:
+    v = 0
+  return v / (-MIN_RSSI)
+
+
+def make_training_data(df: pd.DataFrame, device_to_map):
+  idx_to_tracker = dict(enumerate(df['tracker'].cat.categories ))
+  tracker_to_idx = {v: k for k, v in idx_to_tracker.items()}
+  idx_to_room = dict(enumerate(df['real_room'].cat.categories ))
+  room_to_idx = {v: k for k, v in idx_to_room.items()}
+
+  last_real_room = None
+  start_time = None
+  current_feature = [FAR_AWAY_FEATURE_VALUE] * len(idx_to_tracker)
+  
+  features = []
+  labels = []
+
+  # Feature vectors - rssi column for each room
+  for i, row in df.iterrows():
+    time, device, tracker, rssi, tx_power, real_room = row
+    if device != device_to_map:
+      continue
+    if last_real_room != real_room:
+      start_time = time
+      last_real_room = real_room
+
+    tracker_idx = tracker_to_idx[tracker]
+    current_feature[tracker_idx] = get_feature_value(rssi, tx_power)
+    if time - start_time > 20:
+      features.append(copy(current_feature))
+      labels.append(room_to_idx[real_room])
+
+  return np.array(features), np.array(labels)
+
+def train(features, labels, classes):
+  clf = svm.SVC(kernel='rbf')
+  print("Training")
+  scores = cross_val_score(clf, features, labels, cv=5)
+  print(scores)
+  print("%0.2f accuracy with a standard deviation of %0.2f" % (scores.mean(), scores.std()))
+
+  X_train, X_test, y_train, y_test = train_test_split(features, labels, random_state=0)  
+  clf.fit(X_train, y_train)
+  cm = confusion_matrix(clf.predict(X_test), y_test)
+  print(cm)
+  print(classes)
+  disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=classes)
+  disp.plot()
+  plt.show()
+
+
+
+if __name__ == "__main__":
+  csv_path = Path("/home/martin/code/ansible/roles/bluetooth-monitor/other/collected.csv")
+  df = load_measurements(csv_path)
+  features, labels = make_training_data(df, "martins_apple_watch")
+  print(np.unique(labels))
+  print(features.shape, labels.shape)
+  train(features, labels, list(df['real_room'].dtype.categories))

roles/bluetooth-monitor/other/bt_monitor_server.py

@@ -0,0 +1,309 @@
+#!/usr/bin/env python3
+
+import os
+import aiomqtt
+import json
+import asyncio
+from time import time
+from pathlib import Path
+from collections import namedtuple, defaultdict, deque
+from typing import Dict, Optional, List
+from Crypto.Cipher import AES
+import pandas as pd
+import numpy as np
+import logging
+from sklearn import svm
+from sklearn.model_selection import cross_val_score
+
+logging.basicConfig(level=logging.INFO)
+
+BtleMeasurement = namedtuple("BtleMeasurement", ["time", "tracker", "address", "rssi", "tx_power"])
+BtleDeviceMeasurement = namedtuple("BtleDeviceMeasurement", ["time", "device", "tracker", "rssi", "tx_power"])
+MqttInfo = namedtuple("MqttInfo", ["server", "username", "password"])
+
+# ------------------------------------------------------- DECODING -------------------------------------------------------------------------
+
+
+class DeviceDecoder:
+    """Decode bluetooth addresses - either simple ones (just address to name) or random changing ones like Apple devices using irk keys"""
+
+    def __init__(self, irk_to_devicename: Dict[str, str], address_to_name: Dict[str, str]):
+        """
+        address_to_name: dictionary from bt address as string separated by ":" to a device name
+        irk_to_devicename is dict with irk as a hex string, mapping to device name
+        """
+        self.irk_to_devicename = {bytes.fromhex(k): v for k, v in irk_to_devicename.items()}
+        self.address_to_name = address_to_name
+
+    def _resolve_rpa(rpa: bytes, irk: bytes) -> bool:
+        """Compares the random address rpa to an irk (secret key) and return True if it matches"""
+        assert len(rpa) == 6
+        assert len(irk) == 16
+
+        key = irk
+        plain_text = b"\x00" * 16
+        plain_text = bytearray(plain_text)
+        plain_text[15] = rpa[3]
+        plain_text[14] = rpa[4]
+        plain_text[13] = rpa[5]
+        plain_text = bytes(plain_text)
+
+        cipher = AES.new(key, AES.MODE_ECB)
+        cipher_text = cipher.encrypt(plain_text)
+        return cipher_text[15] == rpa[0] and cipher_text[14] == rpa[1] and cipher_text[13] == rpa[2]
+
+    def _addr_to_bytes(addr: str) -> bytes:
+        """Converts a bluetooth mac address string with semicolons to bytes"""
+        str_without_colons = addr.replace(":", "")
+        bytearr = bytearray.fromhex(str_without_colons)
+        bytearr.reverse()
+        return bytes(bytearr)
+
+    def decode(self, addr: str) -> Optional[str]:
+        """addr is a bluetooth address as a string  e.g. 4d:24:12:12:34:10"""
+        for irk, name in self.irk_to_devicename.items():
+            if DeviceDecoder._resolve_rpa(DeviceDecoder._addr_to_bytes(addr), irk):
+                return name
+        return self.address_to_name.get(addr, None)
+
+    def __call__(self, m: BtleMeasurement) -> Optional[BtleDeviceMeasurement]:
+        decoded_device_name = self.decode(m.address)
+        if not decoded_device_name:
+            return None
+        return BtleDeviceMeasurement(m.time, decoded_device_name, m.tracker, m.rssi, m.tx_power)
+
+
+# ------------------------------------------------------- MACHINE LEARNING  ----------------------------------------------------------------
+
+
+class KnownRoomCsvLogger:
+    """Logs known room measurements to be used later as training data for classifier"""
+
+    def __init__(self, csv_file: Path):
+        self.known_room = None
+
+        if csv_file.exists():
+            self.csv_file_handle = open(csv_file, "a")
+        else:
+            self.csv_file_handle = open(csv_file, "w")
+            print(f"#time,device,tracker,rssi,tx_power,known_room", file=csv_file)
+
+    def update_known_room(self, known_room: str):
+        if known_room != self.known_room:
+            logging.info(f"Updating known_room {self.known_room} -> {known_room}")
+        self.known_room = known_room
+
+    def report_measure(self, m: BtleDeviceMeasurement):
+        ignore_rooms = ("keins", "?", "none", "unknown")
+        if self.known_room is None or self.known_room in ignore_rooms:
+            return
+        logging.info(f"Appending to training set: {m}")            
+        print(
+            f"{m.time},{m.device},{m.tracker},{m.rssi},{m.tx_power},{self.known_room}",
+            file=self.csv_file_handle,)
+
+
+class RunningFeatureVector:
+    FAR_AWAY_FEATURE_VALUE = 1 
+    MIN_TIME_UNTIL_PREDICTION = 40 # wait until every reachable tracker detected the device
+    TIME_TO_DELETE_IF_NOT_SEEN = 30 # if device wasn't spotted for this time period, the measure is set to inf
+
+    def __init__(self, trackers: List[str]):
+        self.trackers = trackers
+        self.feature_vecs_per_device = defaultdict(lambda: [self.FAR_AWAY_FEATURE_VALUE] * len(trackers))
+        self.last_measurements = deque()
+        self.tracker_name_to_idx = {name: i for i, name in enumerate(trackers)}
+        self.start_time = None
+
+    @staticmethod
+    def _get_feature_value(rssi, tx_power):
+        """Transforms rssi and tx power into a value between 0 and 1, where 0 is close and 1 is far away"""
+        MIN_RSSI = -90
+        MAX_TRANSFORMED_RSSI = 40
+        v = tx_power - rssi - MAX_TRANSFORMED_RSSI
+        if v < 0:
+            v = 0
+        return v / (-MIN_RSSI)
+
+    def add_measurement(self, new_measurement: BtleDeviceMeasurement):
+        if self.start_time is None:
+            self.start_time = new_measurement.time
+
+        self.last_measurements.append(new_measurement)
+        while len(self.last_measurements) > 0 and new_measurement.time - self.last_measurements[0].time > self.TIME_TO_DELETE_IF_NOT_SEEN:
+            self.last_measurements.popleft()
+
+        feature_vec = [self.FAR_AWAY_FEATURE_VALUE] * len(self.trackers)
+        for m in self.last_measurements: 
+            if m.device == new_measurement.device:
+                tracker_idx = self.tracker_name_to_idx[m.tracker]
+                feature_vec[tracker_idx] = self._get_feature_value(m.rssi, m.tx_power)
+        return feature_vec if new_measurement.time - self.start_time > self.MIN_TIME_UNTIL_PREDICTION else None
+    
+
+
+def training_data_from_df(df: pd.DataFrame, device_to_train: str):
+    """Returns a feature matrix (num_measurement, num_trackers) and a label vector (both numeric) to be used in scikit learn"""
+    trackers = list(df["tracker"].cat.categories)
+    idx_to_room = dict(enumerate(df["known_room"].cat.categories))
+    room_to_idx = {v: k for k, v in idx_to_room.items()}
+
+    last_known_room = None
+
+    features = []
+    labels = []
+    
+    feature_accumulator = RunningFeatureVector(trackers)
+
+    # Feature vectors - rssi column for each room
+    for i, row in df.iterrows():
+        time, device, tracker, rssi, tx_power, known_room = row
+        m = BtleDeviceMeasurement(time, device, tracker, rssi, tx_power)
+        if device != device_to_train:
+            continue
+        if last_known_room != known_room:
+            feature_accumulator = RunningFeatureVector(trackers) # reset for new room
+            last_known_room = known_room
+        feature_vec = feature_accumulator.add_measurement(m)
+        if feature_vec is not None:
+            features.append(feature_vec)
+            labels.append(room_to_idx[known_room])
+
+    return np.array(features), np.array(labels)
+
+
+def load_measurements_from_csv(csv_file: Path) -> pd.DataFrame:
+    """Load csv with training data into dataframe"""
+
+    def cleanup_column_name(col_name: str):
+        return col_name.replace("#", "").strip()
+
+    df = pd.read_csv(str(csv_file))
+
+    # String cleanup in column names and room names
+    df = df.rename(columns=cleanup_column_name)
+    df.map(lambda x: x.strip() if isinstance(x, str) else x)
+
+    df["tracker"] = df["tracker"].astype("category")
+    df["known_room"] = df["known_room"].astype("category")
+    df['device'] = df['device'].astype("category")
+
+    return df
+
+
+async def send_discovery_messages(mqtt_client, device_names):
+    for device_name in device_names:
+        topic = f"homeassistant/sensor/my_btmonitor/{device_name}/config"
+        msg = {
+            "name": device_name,
+            "state_topic": f"my_btmonitor/ml/{device_name}",
+            "expire_after": 30,
+            "unique_id": device_name,
+        }
+        await mqtt_client.publish(topic, json.dumps(msg).encode(), retain=True)
+
+
+
+async def async_main(
+    mqtt_info: MqttInfo,
+    trackers: List[str],
+    devices: List[str],
+    classifier,
+    device_decoder: DeviceDecoder,
+    training_data_logger: KnownRoomCsvLogger,
+):
+    current_rooms = defaultdict(lambda: "unknown")
+    feature_accumulator = RunningFeatureVector(trackers)    
+    async with aiomqtt.Client(
+        hostname=mqtt_info.server, username=mqtt_info.username, password=mqtt_info.password
+    ) as client:
+        await send_discovery_messages(client, devices)
+        await client.subscribe("my_btmonitor/#")
+        async for message in client.messages:
+            current_time = time()
+            topic = message.topic
+            if topic.value == "my_btmonitor/known_room":
+                training_data_logger.update_known_room(message.payload.decode())
+            else:
+                splitted_topic = message.topic.value.split("/")
+                if splitted_topic[0] == "my_btmonitor" and splitted_topic[1] == "raw_measurements":
+                    msg_json = json.loads(message.payload)
+                    measurement = BtleMeasurement(
+                        time=current_time,
+                        tracker=splitted_topic[2],
+                        address=msg_json["address"],
+                        rssi=msg_json["rssi"],
+                        tx_power=msg_json.get("tx_power", 0),
+                    )
+                    logging.debug(f"Got Measurement {measurement}")
+                    m = device_decoder(measurement)
+                    if m is not None:
+                        logging.info(f"Decoded Measurement {m}")
+                        training_data_logger.report_measure(m)
+                        feature_vec =feature_accumulator.add_measurement(m)
+                        if feature_vec:
+                            feature_str={tracker : value for tracker, value in zip(trackers, feature_vec)} 
+                            logging.info(f"Features: {feature_str}")
+                        if feature_vec is not None and classifier is not None:
+                            room = classifier(m.device, feature_vec)
+                            if room != current_rooms[m.device]:
+                                logging.info(f"{m.device} moved room {current_rooms[m.device]} to {room}")
+                                current_rooms[m.device] = room
+                            await client.publish(f"my_btmonitor/ml/{m.device}", room.encode())
+
+async def async_main_with_restart(
+    mqtt_info: MqttInfo,
+    trackers: List[str],
+    devices: List[str],
+    classifier,
+    device_decoder: DeviceDecoder,
+    training_data_logger: KnownRoomCsvLogger,
+):
+    while True:
+        try:
+            await async_main(mqtt_info, trackers, devices, classifier, device_decoder, training_data_logger)
+        except Exception as e:
+            print(e)
+            print("restarting...")
+
+def get_classification_func(training_df: pd.DataFrame, log_classifier_scores=True):
+    devices_to_track = list(training_df["device"].unique())
+    classifiers = {}
+    rooms = list(training_df["known_room"].dtype.categories)
+    for device_to_track in devices_to_track:
+        features, labels = training_data_from_df(training_df, device_to_track)
+        clf = svm.SVC(kernel="rbf")
+        logging.info(f"Computing cross validation score for {device_to_track}")
+        if log_classifier_scores:
+            scores = cross_val_score(clf, features, labels, cv=5)
+            logging.info("  %0.2f accuracy with a standard deviation of %0.2f" % (scores.mean(), scores.std()))
+
+        logging.info(f"Training SVM classifier for {device_to_track}")
+        clf.fit(features, labels)
+        classifiers[device_to_track] = clf
+
+    def classify(device_name, feature_vec):
+        room_idx = classifiers[device_name].predict([feature_vec])[0]
+        return rooms[room_idx]
+
+    return classify
+
+
+if __name__ == "__main__":
+    mqtt_info = MqttInfo(server="homeassistant.fritz.box", username="my_btmonitor", password="8aBIAC14jaKKbla")
+    # Dict with bt addresses as strings to device name
+    address_to_name = {}
+    # Devices with random addresses - need irk key
+    irk_to_devicename = {
+        "aa67542b82c0e05d65c27fb7e313aba5": "martins_apple_watch",
+        "840e3892644c1ebd1594a9069c14ce0d": "martins_iphone",
+    }
+    script_path = os.path.dirname(os.path.realpath(__file__))
+    data_file = Path(script_path) / Path("training_data.csv")
+    training_df = load_measurements_from_csv(data_file)
+    classification_func = get_classification_func(training_df)
+    training_data_logger = KnownRoomCsvLogger(data_file)
+    device_decoder = DeviceDecoder(irk_to_devicename, address_to_name)
+    trackers = list(training_df["tracker"].cat.categories)
+    devices = list(training_df['device'].cat.categories)
+    asyncio.run(async_main_with_restart(mqtt_info, trackers, devices, classification_func, device_decoder, training_data_logger))

roles/bluetooth-monitor/other/requirements.txt

@@ -0,0 +1,7 @@
+aiomqtt==2.0.0
+numpy==1.26.4
+pandas==2.2.1
+pycryptodome==3.20.0
+scikit-learn==1.4.1.post1
+scipy==1.12.0
+typing_extensions==4.10.0

roles/bluetooth-monitor/templates/my_btmonitor.py

@@ -4,13 +4,12 @@ from bleak import BleakScanner
 from bleak.assigned_numbers import AdvertisementDataType
 from bleak.backends.bluezdbus.advertisement_monitor import OrPattern
 from bleak.backends.bluezdbus.scanner import BlueZScannerArgs 
-from Cryptodome.Cipher import AES
 from functools import partial
 import asyncio_mqtt
 import json
-from typing import Dict
-import collections
-import numpy as np
+from datetime import datetime
+import os
+import time
 
 # ------------------- Config ----------------------------------------------------------------
 
@@ -21,116 +20,51 @@ config = {
     "password": "{{my_btmonitor_mqtt_password}}",
     "room": "{{sensor_room_name_ascii}}"
   },
-  "irk_to_devicename": {
-    "aa67542b82c0e05d65c27fb7e313aba5": "martins_apple_watch",
-    "840e3892644c1ebd1594a9069c14ce0d" : "martins_iphone",
-  }
+  "watchdog_seconds": {{my_bt_monitor_watchdog_seconds | default(None)}},
+  "restart_ble_interface": {{my_btmonitor_restart_ble_interface | default(None)}},
 }
 
-# --------------------------------------------------------------------------------------------
-
-def resolve_rpa(rpa: bytes, irk: bytes) -> bool:
-  """Compares the random address rpa to an irk (secret key) and return True if it matches"""
-  assert len(rpa) == 6
-  assert len(irk) == 16
-
-  key = irk
-  plain_text = b'\x00' * 16
-  plain_text = bytearray(plain_text)
-  plain_text[15] = rpa[3]
-  plain_text[14] = rpa[4]
-  plain_text[13] = rpa[5]
-  plain_text = bytes(plain_text)
-
-  cipher = AES.new(key, AES.MODE_ECB)
-  cipher_text = cipher.encrypt(plain_text)
-  return cipher_text[15] == rpa[0] and cipher_text[14] == rpa[1] and cipher_text[13] == rpa[2]
+stop_event = asyncio.Event()
+time_last_package_received = datetime.now()
 
 
-def addr_to_bytes(addr:str) -> bytes:
-  """Converts a bluetooth mac address string with semicolons to bytes"""
-  str_without_colons = addr.replace(":", "")
-  bytearr =  bytearray.fromhex(str_without_colons)
-  bytearr.reverse()
-  return bytes(bytearr)
-
-
-def decode_address(addr: str, irks: Dict[str, str]):
-  """
-  addr is a bluetooth address as a string  e.g. 4d:24:12:12:34:10
-  irks is dict with irk as a hex string, mapping to device name
-  """
-  for irk, name in irks.items():
-    if resolve_rpa(addr_to_bytes(addr), bytes.fromhex(irk)):
-      return name
-  return None
-
-
-def estimate_distance(rssi, tx_power, pl0=73):
-  """
-  RSSI in dBm
-  txPower is a transmitter parameter that calculated according to its physic layer and antenna in dBm
-  Return value in meter
-
-  You should calculate "PL0" in calibration stage:
-  PL0 = txPower - RSSI; // When distance is distance0 (distance0 = 1m or more)
-
-  SO, RSSI will be calculated by below formula:
-  RSSI = txPower - PL0 - 10 * n * log(distance/distance0) - G(t)
-  G(t) ~= 0 //This parameter is the main challenge in achiving to more accuracy.
-  n = 2 (Path Loss Exponent, in the free space is 2)
-  distance0 = 1 (m)
-  distance = 10 ^ ((txPower - RSSI - PL0 ) / (10 * n))
-
-  Read more details:
-     https://en.wikipedia.org/wiki/Log-distance_path_loss_model
-  """
-  n = 3.5
-  return 10**((tx_power - rssi - pl0) / (10 * n))
-
-
-def smooth(y, box_pts):
-    box = np.ones(box_pts)/box_pts
-    y_smooth = np.convolve(y, box, mode='same')
-    return y_smooth
-
-WINDOW_SIZE = 6
-last_values = collections.deque(maxlen=WINDOW_SIZE)
-def filter_distance(dist: float):
-  global last_values
-  last_values.append(dist)
-  return smooth(np.array(last_values), 12)[-1]
-
-
-async def on_device_found_callback(irks, mqtt_client, room, device, advertising_data):
-  decoded_device_id = decode_address(device.address, irks)
+async def on_device_found_callback(mqtt_client, room, device, advertising_data):
+  global time_last_package_received
+  time_last_package_received = datetime.now()
   rssi = advertising_data.rssi
   tx_power = advertising_data.tx_power
-  if decoded_device_id and tx_power is not None and rssi is not None:
-    topic = f"my_btmonitor/devices/{decoded_device_id}/{room}"
-    distance = estimate_distance(rssi, tx_power, {{my_btmonitor_pl0 | default('73')}} )
-    filtered_distance = filter_distance(distance)
-    data = {"id": decoded_device_id, 
-            "name": decoded_device_id, 
+  if  tx_power is not None and rssi is not None:
+    topic = f"my_btmonitor/raw_measurements/{room}"
+    data = {"address": device.address,
             "rssi": rssi, 
-            "tx_power": tx_power,
-            "distance": filtered_distance,
-            "unfiltered_distance": distance,
-    }
-    await mqtt_client.publish(topic, json.dumps(data).encode())
-    #print(data)
+            "tx_power": tx_power}
+    try:
+      await mqtt_client.publish(topic, json.dumps(data).encode())
+    except Exception:
+      print("Probably mqtt isn't running - exit whole script and let systemd restart it")
+      exit(1)
 
 
-async def main():
-    stop_event = asyncio.Event()
+async def watchdog():
+  global time_last_package_received
+  timeout = config["watchdog_seconds"]
+  if not timeout or timeout <= 0:
+    return
+  while True:
+    restart = (datetime.now() - time_last_package_received).seconds > timeout
+    if restart:
+      stop_event.set()
+    await asyncio.sleep(60) 
 
+
+async def ble_scan():
     mqtt_conf = config['mqtt']
     while True:
       try:
         async with asyncio_mqtt.Client(hostname=mqtt_conf["hostname"], 
-                                      username=mqtt_conf["username"], 
-                                      password=mqtt_conf['password']) as mqtt_client:
-          cb = partial(on_device_found_callback, config['irk_to_devicename'], mqtt_client, mqtt_conf['room'])
+                                       username=mqtt_conf["username"], 
+                                       password=mqtt_conf['password']) as mqtt_client:
+          cb = partial(on_device_found_callback, mqtt_client, mqtt_conf['room'])
           active_scan = True
           if active_scan:
             async with BleakScanner(cb) as scanner:
@@ -146,4 +80,18 @@ async def main():
         print("Error", e)              
         print("Starting again")
 
-asyncio.run(main())
+
+async def main():
+  await asyncio.gather(ble_scan(), watchdog())
+
+
+if __name__ == "__main__":
+  restart_interface = config["restart_ble_interface"]
+  if restart_interface:
+    print(f"Restarting {restart_interface}")
+    os.system(f"hciconfig {restart_interface} down")
+    time.sleep(3)
+    os.system(f"hciconfig {restart_interface} up")
+    time.sleep(3)
+    print("Done")
+  asyncio.run(main())

roles/pi-better-shell-env/tasks/main.yml

@@ -1,36 +0,0 @@
----
-- name: Install packages
-  apt:
-    name:
-      - bat
-      - fish
-      - fzf
-      - fd-find
-      - ripgrep
-      - lsd
-      - zoxide
-
-- name: Check if oh-my-fish is installed
-  stat:
-    path: '/etc/omf.installed'
-  register: omf
-
-- name: Download omf installer
-  get_url: 
-    url: https://raw.githubusercontent.com/oh-my-fish/oh-my-fish/master/bin/install
-    
-- name: Execute omf installer
-  shell: /usr/bin/fish /tmp/install --noninteractive
-
-- name: Execute omf installer
-  shell: /usr/bin/fish -c omf install
-
-- name: Remove the omf installer
-  file: 
-    path: /tmp/install
-    state: absent
-
-- name: Mark oh-my-fish installed with /etc/omf.installed
-  file:
-    path: /etc/omf.installed
-    state: touch

roles/pi-musicmouse/files/config.yml

@@ -0,0 +1,40 @@
+general:
+  alsa_device: softvol_effects
+  mqtt:
+    user: musicmouse
+    password: KNLEFLZF94yA6Zhj141
+    server: homeassistant 
+  hass_url: https://ha.bauer.tech
+  hass_token: "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiI4N2ExMzM2ZmQ4ZWQ0ZDgzOWZhMjU3NmZjYTg1NWQ1ZiIsImlhdCI6MTcwNDAyOTUyOSwiZXhwIjoyMDE5Mzg5NTI5fQ.vx9L5bTSey98uc8TwodShaEXSMr-hjXugPsNviR_fEw" 
+  button_leds_brightness: 0.5
+  volume_increment: 5
+  min_volume: 23
+  max_volume: 70
+  serial_port: "/dev/ttyUSB0"
+
+figures:
+  elefant:       
+    id: "88041174e9"
+    colors: ["#ffff00", "#00c8ff", "#094b46", "#c20099"]
+  fuchs: 
+     id: "8804ce7230"
+     colors: ["#F4D35E", "#F95738", "#F95738", "#083d77"]
+  eule:          
+      id: "88040d71f0"
+      colors: ["#e5a200", "#f8e300", "w33", "w99"]
+  omnom:         
+      id: "88043c6ede"
+      colors: ["#005102", "#fec800", "#005102", "#3bc405"]
+  eichhoernchen:
+      id: "88040b78ff"
+      colors: ["#ff0ada", "#4BC6B9", "#69045a", "#4BC6B9"] 
+  hund:          
+      id: "8804bc7444"
+      colors: ["#ffff00", "#00c8ff", "#094b46", "#c20099"]
+  hase:
+      id: "88044670ba"
+      colors: ["#ffff00", "#00c8ff", "#094b46", "#c20099"]
+  schneemann:
+      id: "88043f71c2"
+      colors: ["#ff0ada", "#4BC6B9", "#69045a", "#4BC6B9"] 
+

roles/pi-musicmouse/files/musicmouse.service

@@ -0,0 +1,11 @@
+[Unit]
+Description=MusicMouse Player
+After=network.target
+
+[Service]
+Type=simple
+Restart=always
+ExecStart=/opt/musicmouse_venv/bin/python /opt/musicmouse/espmusicmouse/host_driver/main.py /media/musicmouse/
+
+[Install]
+WantedBy=multi-user.target

roles/pi-musicmouse/files/smb.conf

@@ -0,0 +1,15 @@
+[global]
+  workgroup = WORKGROUP
+  logging = syslog@1
+  server role = standalone server
+  obey pam restrictions = no
+  unix password sync = no
+
+
+[MusicMouse]
+   browseable = yes
+   path = /media/musicmouse
+   guest ok = no
+   writeable = yes
+   create mask = 666
+   force create mode = 666

roles/pi-musicmouse/tasks/main.yml

@@ -0,0 +1,38 @@
+---
+- name: Packages
+  apt:
+    name: 
+      - python3
+      - python3-pip
+      - python3-vlc # also in venv - but this installs vlc + deps
+      - samba
+- name: Checkout Musicmouse repo
+  ansible.builtin.git:
+    repo: 'ssh://git@git.bauer.tech:2222/martin/musicmouse.git'
+    dest: '/opt/musicmouse'
+    version: 'release/1.1'
+    accept_hostkey: true
+- name: Create and update virtual env
+  ansible.builtin.pip:
+    requirements: /opt/musicmouse/espmusicmouse/host_driver/requirements.txt
+    virtualenv: /opt/musicmouse_venv
+    virtualenv_command: "/usr/bin/python3 -m venv"
+- name: Create media directory
+  file:
+    path: /media/musicmouse
+    state: directory
+- name: Install config file
+  copy: src=config.yml dest=/media/musicmouse/config.yml
+- name: Install systemd service file
+  copy: src=musicmouse.service dest=/etc/systemd/system/
+- name: Add script to autostart and start now
+  systemd: name=musicmouse state=restarted enabled=yes daemon_reload=yes
+- name: Samba setup
+  copy: src=smb.conf dest=/etc/samba/
+- name: Restart samba
+  systemd: name=smbd state=restarted enabled=yes 
+# manual steps: 
+#    - set samba passwords with smbpasswd
+#    - copy music into /media/musicmouse (or via samba share)
+#    - upload host driver?
+#    - manual patching of hassclient necessary :( loop has to be passed in, to not use running_event_loop

todo.md

@@ -23,3 +23,13 @@ dpkg-buildpackage -b -uc
 [General]
 Discoverable=false
 Alias=bla
+
+
+Environment:
+- fish 
+  - apt install fish
+- oh my fish
+- fish config
+- ripgrep (apt install ripgrep)
+- fd (apt install fd-find) 
+- apt install neovim tmux fd-find ripgrep lsd broot fzf tmux glances

working.yml

@@ -18,3 +18,16 @@
     - pi-disable-onboard-bluetooth
     - bluetooth-monitor
 
+- hosts: musicmouse
+  roles:
+    - pi-standard-setup
+    - pi-hifiberry-amp
+    - pi-musicmouse
+    - pi-squeezelite-custom
+    - pi-shairport
+    - pi-lirc
+    - bluetooth-monitor
+
+- hosts: homeassistant
+  roles:
+    - bluetooth-monitor