LoRaSoundkit

Open source (hardware) sound level meter for the internet of things.

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

General

This Soundkit sensor measures continuously audible sound by analyzing the data using FFT. The results are send each minute to the LoRa network. The sensor measures audible spectrum from 31.5 Hz to 8 kHz divided in 9 octaves. Also each minute the average, minimum and maximum levels are calculated for the 3 weighting curves dB(A), dB(C) and db(Z).

Sound Kit Sparkfun board

Sound Kit TTGO board

Sound Kit TTGO OLED display

Electronic components assembly

The software is based on ESP32 processor with Lora module. Two boards has been tested viz. Sparkfun LoRa board and TTGO LoRa board. The TTGO LoRa board does have an OLED display, and will display the average dB(A), dB(C) and dB(z) levels.

Components

• Sparkfun LoRa Gateway 1-channel ESP32 (used as Sensor), or TTGO LoRa32 V1
• I2S MEMS microphone SPH046 or I2S MEMS microphone NMP441
• antenna ¼ lambda, e.g a wire of 8.4 cm length or 868MHz Helical Antenna
• power adapter 5V, 0.5A

The table below shows the wiring between MEMS microphone (SPH0645 or NMP443) and the processor board (Sparkfun or TTGO):

SPH0645	NMP442		Sparkfun	TTGO
3V	3V	<-->	3V	3V
GND	GND	<-->	GND	GND
BCLK	SCK	<-->	GPIO18	GPIO13
DOUT	SD	<-->	GPIO19	GPIO35
LRCL	WS	<-->	GPIO23	GPIO12
	LR	GND
SEL		not connected

N.B.

For sound measurements lower then 30 dB, the supply to the MEMS microphone must be very clean. The 3V supplied by the Sparkfun ESP gives in my situation some rumble in low frequencies. It can be uncoupled by extra 100nf and 100 uF or a separate 3.3V stabilzer.

Driver in Windows

For uploading to the device, it needs to be recognised by Windows. If the default driver is not installed correctly, you can use the CP210x Universal Windows Driver.

Board configuration in PlatformIO

Choose your board in the platformio.ini file and change "default_envs" in one of the two lines below:

• default_envs = ttgo
• default_envs = sparkfun

Board configuration in 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 your board you want to use:

• Select TTGO LoRa32-OLED V1 board or
• Select Sparkfun LoRa Gateway 1-Channel board

The Sounkit sourcecode supports both boards. If Sparkfun Lora gateway is not vissible check the presence of the Sparkfun variant file, see instructions at https://learn.sparkfun.com/tutorials/sparkfun-lora-gateway-1-channel-hookup-guide/programming-the-esp32-with-arduino

Libraries

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

LMIC

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\ or use the Library Manger MCCI Arduino LoraWAN Library and its dependency MCCI LoraWAN LMIC Library.

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

Monochrome OLED library

For the TTGO board, download the libraries below and put them in your [Arduino-path]\libraries or use the Library Manager Adafruit SSD1306 and Adafruit GFX Library.

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

Arduino FFT

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

Optional for debugging: LibPrintf

When debugging code and using the Serial Monitor, you need LibPrintf to display debug messages.

Config file

In the config.h some parameters are defined.

Cycle count

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

#define CYCLECOUNT   60000 

LoRa TTN keys

The device address and keys have to be set to the ones generated in the TTN console. Login in the TTN console and add your device. Choose activation mode OTAA and copy the APPEUI, DEVEUI and APPKEY keys into this config file:

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

Screen options

When using the soundkit with a screen, you have an option to show a progressbar when the next LoRa upload will be. In addition you can choose if the screen shows dB(A), dB(C), dB(Z), or min/max/avg of dB(Z).

#define SHOWMINMAX false
#define SHOWCYCLEPROGRESS true

Connecting to LoRa

When starting the device, it can take a while before it successfully connects to LoRa (about an hour). Every cyclecount, the device tries to login to TTN. Under the hood the message is EV_JOIN_TXCOMPLETE: no JoinAccept. It could help to change ClockError value, but it didn't help for me. When debugging, you can disable the connection to TTN.

#define CONNECTTOLORA	true

Specification

Sound Measuerment

• 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

Interface

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 messsage to a readable JSON message. Copy the payload_ttn.js code and paste in the TheThingsNetwork-console as a decoder. The decoder will computer dB(A) and dB(C) spectrum values from the dB(Z) spectrum values.

Example of a decoded 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
    ]
  }
}

Example graphical output Sound Kit

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.