噓！嫌鄰居放歌太吵，開發者偷用「樹莓派+AI」黑進音箱：幹擾音頻，使其不得不關

編譯 | 鄭麗媛

出品 | CSDN（ID：CSDNnews）

試問：如果你一牆之隔的鄰居總是在每天早上 9 點用藍牙音箱以最大音量播放雷鬼音樂（Reggaeton），你會怎麼辦？

A. 去隔壁敲門，禮貌地請他們降低音量。

B. 聯系物業，要求物業進行溝通處理。

開發者 Roni Bandin 就面對着這樣的處境，而他的選擇是 C：利用 Raspberry Pi（樹莓派）和 AI 技術，做一個能更有創意地處理這種情況的 AI 裝置——當這台 Raspberry Pi 檢測到有雷鬼音樂時，它就會幹擾附近的藍牙音箱，使音頻失真以此來屏蔽鄰居的“嘈雜音樂”。

初步設計

根據 Roni Bandin 介紹，他将這款裝置取名為 Reggaeton Be Gone（雷鬼消失）。它主要負責監控房間内的音頻，通過機器學習識别雷鬼音樂，一旦識别就向藍牙音箱觸發通信請求和資料包。

簡而言之，Reggaeton Be Gone 的設計目标是：禁用播放雷鬼音樂的音箱，或者至少要把聲音擾亂到鄰居不得不關閉音箱的程度。有了初步想法後，Roni Bandin 畫了一張設計草圖：

其中，有關 Reggaeton Be Gone 的硬體組成部分如下：

樹莓派 3B+：樹莓派 3B+ 是樹莓派 3 系列中的最新産品，配備 64 位四核處理器，運作頻率為 1.4GHz，具有雙頻 2.4GHz 和 5GHz 無線區域網路、藍牙 4.2/BLE、更快的以太網和通過單獨的 PoE HAT 實作 PoE 功能。

DFRobot 小型 OLED 螢幕：螢幕尺寸為 0.91 英寸的 OLED 顯示屏，分辨率為 128x32 像素；采用 IIC 的接口，工作電壓為 3.3-5V，全屏的最大功耗為 25Ma 左右。

DFRobot Gravity 數字大按鈕子產品（黃色）：相容 5/3.3V 電壓，适應 Arduino 新一代主要 DUE。

除此之外，還有 USB 麥克風或帶麥克風的聲霸卡（用來觀察音頻，Roni Bandin 用的是 Behringer Xenyx302）、microSD 卡、5v 3A 電源、母頭連接配接母頭的跨接線和 3D 列印的外殼正面（Roni Bandin 用的是一塊從破損音頻闆上拆下的金屬外殼）。另外，Roni Bandin 還補充道：如果你想用自己的 BT 進行測試，還可以買一個便宜的藍牙音頻接收器電路闆。

具體如何實作的？

電路圖

硬體準備到位後，Roni Bandin 首先按照電路圖連接配接了各部件：

（1）按鈕連接配接到 GND 和 GPIO 26

（2）OLED 螢幕連接配接到 VCC、GND、SDA GPIO 2 和 SDL GPIO 3

（3）将聲霸卡或麥克風連接配接到 USB 

軟體設定

緊接着，他安裝了樹莓派作業系統（https://www.raspberrypi.com/software/），執行 sudo raspi-config，并啟用 SSH 和 i2c。然後進行一些必要設定：

pip install RPi.GPIO

pip3 install Adafruit_GPIO

sudo apt install git

pip install picamera

sudo apt install python3-opencv

sudo apt-get install libatlas-base-dev libportaudio0 libportaudio2 libportaudiocpp0 portaudio19-dev

git clone https://github.com/edgeimpulse/linux-sdk-python

sudo python3 -m pip install edge_impulse_linux -i https://pypi.python.org/simple

sudo python3 -m pip install numpy

sudo python3 -m pip install pyaudio

由 i2cdetect -y 1 檢查是否檢測到 Oled 螢幕，還應運作 alsamixer 并按 F6 鍵選擇電路闆，按 F4 鍵更改輸入音量。

機器學習

在機器學習（ML）方面，Roni Bandin 對神經網絡進行如下設定：

GTZAN 是非常經典的音樂資料集，但其中沒有雷鬼音樂類别的 AI 分類資料集和模型，于是 Roni Bandin 決定自己訓練模型：“Reggaeton 的經典切分節奏模式可能很吵，但這種特點也非常有利于機器學習。”

為此，Roni Bandin 下載下傳了幾首雷鬼音樂和其他類型的歌曲，并将其導出為 16khz wav 格式，上傳到 Edge Impulse 平台（一個使用者友好的開發平台，用于在邊緣裝置上進行機器學習，涵蓋 TinyML 學習路徑所需的從資料收集到模型部署的整個流程 ）。然後，他為 Linux ARM 進行了部署，導出 eim 檔案并傳入樹莓派，将權限改為 744。Roni Bandin 表示，不久後他會釋出該模型，感興趣的人可以耐心等待。

Python 代碼

Python 代碼将采集音頻樣本，并将其發送至 ML 模型進行推理。如果識别到雷鬼音樂的得分高于門檻值，就會觸發兩種 BT 連接配接方法中的一種。其中一種使用 rfconn，另一種使用 l2ping。日志檔案會被儲存，而裝置運作情況将顯示在 OLED 螢幕上。

設定配置如下，此外 Roni Bandin 提醒：“你最好通過反複試驗來确定最佳方法、封裝尺寸和線數。如果能用帶天線的外置 BT 闆，那最好不過了。”

myPath="" # reggaeton be gone folder

selectedDeviceId = 1 # id of the USB mic of board

method = 1 # 1 to 3 # BT attack method

targetAddr = "" # mac address of the BT speaker

packagesSize = 0 # packet size, try around 600-1000

threadsCount = 0 # how many

threshold = 0.95 # limit to consider that the song is reggaeton

myDelay = 0.1 # delay between connections

forceFire = 1 # test purposes

model = ".eim" # model file name

如何擷取 BT 揚聲器的 MAC 位址

針對這個問題，Roni Bandin 給出了兩種方法：

（1）如果是用自己的 BT 揚聲器進行測試，可連接配接智能手機并從連接配接資訊中檢視 MAC；

（2）如果不是，可使用 bluetoothctl 指令，根據資訊、rssi 功率等資訊猜測目标 MAC 位址。

sudo bluetoothctl

scan on

通過第二種方法，開發者将獲得 2 列 MAC 位址，有時還有揚聲器辨別符，如 POCKETTUNE、AUVIO 等，然後可執行下面指令，通過 RSSI 資訊确定 MAC 位址：

sudo btmon |grep RSSI & sudo hcitool scan

and get RSSI

與此同時，名為 log.txt 的檔案将記錄所有裝置操作。

最終成果

至此，這款名為 Reggaeton Be Gone 的裝置就大緻完成了。Roni Bandin 錄制了一段該裝置的最終表現：能準确識别播放的歌曲是否屬于雷鬼音樂，在确定是雷鬼音樂後，成功幹擾了藍牙音箱的音頻。

不過，Roni Bandin 也強調 Reggaeton Be Gone 隻是一個實驗項目，可基于教學目的用作參考，效仿之前也請“仔細查閱當地法律法規”。此外，該裝置起作用的前提是離揚聲器足夠近，且并非所有的藍牙揚聲器都容易受到攻擊。

參考連結：

https://www.hackster.io/roni-bandini/reggaeton-be-gone-e5b6e2

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