gachet / sound-sensor Goto Github PK

• General
• Electronic components assembly
• Board configuration
• Libraries
• Config file
• Specification
• Example graphical output Sound Kit
• Last Updates
• To Do

This Soundkit is easy to build for a low cost price (ca. 40 euro) and is therefore very suitable to be used for citizen sensing.

This sensor measures continuously audible sound by analyzing the data using FFT process. The measured results are send in a report at regular time intervals to the LoRaWan network, where it can be picked up for visualization.

No adjustments are needed, because the sensor uses a digital MEMS microphone. which is factory calibrated. Furthermore it can easily be connected to the community network, viz. it is independent of a home or office network.

The sensor make use of the powerful ESP32 processor, which is a dual core processor. One core handles continuously the processing of audio, while the other core handles the LoRaWan communication.

The sensor measures audible spectrum from 31.5 Hz to 8 kHz divided in 9 octaves. Each regular time interval the average, minimum and maximum levels are calculated for the 3 weighting curves dB(A), dB(C) and db(Z).

Sound Kit TTGO board

Sound Kit TTGO OLED display

The software is based on TTGO LoRa board, this board includes a ESP32 processor, a Lora RFM95 module, LoRa antenna. The TTGO LoRa board does have an OLED display, and will display the average dB(A), dB(C) and dB(z) levels.

I have tested two MEMS microphones viz. SPH0645 and INMP441. The SPH0645 was slightly better in low frequencies. This is more important if you want to measure db(C) and db(Z) levels.

• Processor board: TTGO LoRa32 V1
• I2S Microphone: SPH0645 or INMP441
• power adapter 5V, 0.5A

The table below shows the wiring between MEMS microphone (SPH0645 or INMP441) and the processor board TTGO:

Remark 1:

The length of the wires between MEMS and TTGO-board should not exceed 15 cm and tie the wires close to each other, or use a 5 wire flat cable.

Remark 2

For sound measurements lower then 30 dB, the power to the MEMS microphone must be very clean. The 3.3V supplied to the MEMS can cause some rumble in low frequencies. It can be improved by placing an extra 100nf and 100 uF capacitor in parallel or use a separate 3.3V stabilizer.

PlatformIO Choose your board in the platformio.ini file and change "default_envs" in the line below:

default_envs = ttgo

Arduino Install ESP32 Arduino Core Add the line in Arduino→preferences→Additional Boardsmanagers URL:

https://dl.espressif.com/dl/package_esp32_index.json

Restart Arduino environment. In the Arduino menu Tools→Boards, choose the board TTGO LoRa32-OLED V1

If you develop in PlatformIO, you can skip this section, libraries and macros are defined in platformio.ini and are installed automatically.

There are several LIMC LoRaWan libraries. I use the LMIC library from MCCI-Catena, because this one is currently best maintained. Download the library from https://github.com/mcci-catena/arduino-lmic and put it in your <arduino-path>\libraries\

Take care that you change the frequency plan to Europe (if you are in Europe), because it is defaulted to the US. It can be changed in the file <arduino-path>\arduino-lmic-master\project_config\lmic_project_config.h

#define CFG_eu868 1

For the TTGO board, download the libraries below and put them in your [Arduino-path]\libraries

https://github.com/adafruit/Adafruit_SSD1306
https://github.com/adafruit/Adafruit-GFX-Library

I used the https://www.arduinolibraries.info/libraries/arduino-fft library. The two files “arduinoFFT.h” and arduinoFFT.ccp” are already in your .ino main directory.

In the config.h some parameters are defined.

The cycle count defines how often a measurement is sent to the thingsnetwork in seconds:

#define CYCLETIME   60

For RIVM and sensor.community use 150

TTN V2 stops at the end of 2021, so my advice is use the TTN console V3 to set your keys.
Register your device, choose 'manually' and MAC version 1.03. Choose activation mode OTAA and copy the the (generated) APPEUI and APPKEY keys into this config file (config,h):

#define APPEUI "0000000000000000"
#define APPKEY "00000000000000000000000000000000"

Note that unique DEVEUI is read from the TTGO ESP32 board id. The DEVEUI is displayed in the TTGO log during startup and is displayed on the OLED display. This value must be entered in the TTN console in the field DEVEUI.

• sample frequency MEMS microphone 22.628 kHz
• 18 bits per sample
• soundbuffer 2048 samples
• FFT bands in bins of 11 Hz (22628 / 2048)
• measurement cycle time 90 msec
• one measurement contains
  • spectrum 31.5Hz, 63Hz, 123Hz, 250Hz, 500 Hz, 1kHz, 2kHz, 4kHz and 8kHz
  • average, maximum and minimum level

Every minute a message is composed from all measurements done in one minute, which contains the following values in dB.

• 9 spectrum levels for dB(A)
• 9 spectrum levels for dB(C)
• 9 spectrum levels for dB(Z)
• min, max, and average levels for dB(A)
• min, max, and average levels for dB(C)
• min, max, and average levels for dB(Z)

The message is send in a compressed binary format to TTN. The TTN payload decoder converts the message to a readable JSON message.

  "la": {
    "avg": 44.2,
    "max": 50.4,
    "min": 39.8,
    "spectrum": [
      22.2,
      30.4,
      37.1,
      36,
      35,
      35.3,
      34.3,
      37.4,
      30.5
    ]
  },
  "lc": {
    "avg": 61.3,
    "max": 72.5,
    "min": 49.5,
    "spectrum": [
      58.6,
      55.8,
      53,
      44.6,
      38.2,
      35.3,
      33.3,
      36.6,
      28.6
    ]
  },
  "lz": {
    "avg": 63.4,
    "max": 75.1,
    "min": 50.3,
    "spectrum": [
      61.6,
      56.6,
      53.2,
      44.6,
      38.2,
      35.3,
      33.1,
      36.4,
      31.6
    ]
  }
}

Below a graph of a sound measurement in my living room in dB(A). In this graph some remarkable items are vissible:

• blue line shows the max level of the belling comtoise clock each half hour
• visible noise of the dishing machine from 0:30 to 1:30
• noise of of the fridge the 125 Hz line
• incrementing outside traffic (63 Hz) at 7.00

The green blocks shows the average spectrum levels. This graph is made with Nodered, InfluxDb and Grafana.

Changed 15-8-2021

• MCCI Catena LoRa stack
• Worker loop changed (hang situation solved with TTN V3)
• OLED display added
• DEVEUI obtained from BoardID, (same SW for multiple sensors)
• use the TWO processor cores of ESP (one core for audio and one core for LoRa)
• DC offset MEMS compensated by moving average window
• payload compressed from 27 to 19 bytes

Advice for sensor housing and microphone placement.

Provide a test document to validate the sensor for use in communities (sensor.community and RIVM)