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stas-sl committed Oct 8, 2024
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---
rules:
line-length:
max: 100
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280 changes: 141 additions & 139 deletions README.md
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Expand Up @@ -8,22 +8,33 @@ Typical weekly traffic noise recorded with a microphone located 50m from a mediu

<img width="1187" alt="image" src="https://user-images.githubusercontent.com/4602302/224789124-a86224c9-c11d-4972-a564-b042bab97bcb.png">


## Configuration

Add it to your ESPHome config:

```yaml
external_components:
- source: github://stas-sl/esphome-sound-level-meter # add @tag if you want to use a specific version (e.g @v1.0.0)
```
For configuration options see [minimal-example-config.yaml](configs/minimal-example-config.yaml) or [advanced-example-config.yaml](configs/advanced-example-config.yaml):
For configuration options see [minimal-example-config.yaml](configs/minimal-example-config.yaml) or [advanced-example-config.yaml](configs/advanced-example-config.yaml). I would recommend starting from minimal config and if it works and produces reasonable values (30-100 dB SPL), then add more filters/sensors.
```yaml
i2s:
bck_pin: 23

bck_pin: 23 # also labeled as SCK
ws_pin: 18
din_pin: 19
din_pin: 19 # also labeled as SD
sample_rate: 48000 # default: 48000
bits_per_sample: 32 # default: 32

# Common settings are bits_per_sample: 16 and bits_shift: 0,
# which should work for most microphones. A 16-bit resolution provides
# a 96 dB dynamic range, sufficient to cover the dynamic range of most
# MEMS microphones.
# Alternatively, if your mic supports 24 bit resolution, you can
# try bits_per_sample: 32 and bits_shift: 8
bits_per_sample: 16 # default: 16
dma_buf_count: 8 # default: 8
dma_buf_len: 256 # default: 256
use_apll: true # default: false
Expand All @@ -38,7 +49,7 @@ i2s:
# for example if mic has 24 bit resolution, and
# i2s configured as 32 bits, then audio data will be aligned left (MSB)
# and LSB will be padded with zeros, so you might want to shift them right by 8 bits
bits_shift: 8 # default: 0
bits_shift: 0 # default: 0

sound_level_meter:
id: sound_level_meter1
Expand Down Expand Up @@ -76,136 +87,125 @@ sound_level_meter:
# additional offset if needed
offset: 0dB # default: empty

# for flexibility sensors are organized hierarchically into groups. each group
# could have any number of filters, sensors and nested groups.
# for examples if there is a top level group A with filter A and nested group B
# with filter B, then for sensors inside group B filters A and then B will be
# applied:
# groups:
# # group A
# - filters:
# - filter A
# groups:
# # group B
# - filters:
# - filter B
# sensors:
# - sensor X
groups:
# group 1 (mic eq)
- filters:
# for now only SOS filter type is supported, see math/filter-design.ipynb
# to learn how to create or convert other filter types to SOS
- type: sos
coeffs:
# INMP441:
# b0 b1 b2 a1 a2
- [ 1.0019784 , -1.9908513 , 0.9889158 , -1.9951786 , 0.99518436]

# nested groups
groups:
# group 1.1 (no weighting)
- sensors:
# 'eq' type sensor calculates Leq (average) sound level over specified period
- type: eq
name: LZeq_1s
id: LZeq_1s
# you can override updated_interval specified on top level
# individually per each sensor
update_interval: 1s

# you can have as many sensors of same type, but with different
# other parameters (e.g. update_interval) as needed
- type: eq
name: LZeq_1min
id: LZeq_1min
unit_of_measurement: dBZ

# 'max' sensor type calculates Lmax with specified window_size.
# for example, if update_interval is 60s and window_size is 1s
# then it will calculate 60 Leq values for each second of audio data
# and the result will be max of them
- type: max
name: LZmax_1s_1min
id: LZmax_1s_1min
window_size: 1s
unit_of_measurement: dBZ

# same as 'max', but 'min'
- type: min
name: LZmin_1s_1min
id: LZmin_1s_1min
window_size: 1s
unit_of_measurement: dBZ

# it finds max single sample over whole update_interval
- type: peak
name: LZpeak_1min
id: LZpeak_1min
unit_of_measurement: dBZ

# group 1.2 (A-weighting)
- filters:
# for now only SOS filter type is supported, see math/filter-design.ipynb
# to learn how to create or convert other filter types to SOS
- type: sos
coeffs:
# A-weighting:
# b0 b1 b2 a1 a2
- [ 0.16999495 , 0.741029 , 0.52548885 , -0.11321865 , -0.056549273]
- [ 1. , -2.00027 , 1.0002706 , -0.03433284 , -0.79215795 ]
- [ 1. , -0.709303 , -0.29071867 , -1.9822421 , 0.9822986 ]
sensors:
- type: eq
name: LAeq_1min
id: LAeq_1min
unit_of_measurement: dBA
- type: max
name: LAmax_1s_1min
id: LAmax_1s_1min
window_size: 1s
unit_of_measurement: dBA
- type: min
name: LAmin_1s_1min
id: LAmin_1s_1min
window_size: 1s
unit_of_measurement: dBA
- type: peak
name: LApeak_1min
id: LApeak_1min
unit_of_measurement: dBA

# group 1.3 (C-weighting)
- filters:
# for now only SOS filter type is supported, see math/filter-design.ipynb
# to learn how to create or convert other filter types to SOS
- type: sos
coeffs:
# C-weighting:
# b0 b1 b2 a1 a2
- [-0.49651518 , -0.12296628 , -0.0076134163, -0.37165618 , 0.03453208 ]
- [ 1. , 1.3294908 , 0.44188643 , 1.2312505 , 0.37899444 ]
- [ 1. , -2. , 1. , -1.9946145 , 0.9946217 ]
sensors:
- type: eq
name: LCeq_1min
id: LCeq_1min
unit_of_measurement: dBC
- type: max
name: LCmax_1s_1min
id: LCmax_1s_1min
window_size: 1s
unit_of_measurement: dBC
- type: min
name: LCmin_1s_1min
id: LCmin_1s_1min
window_size: 1s
unit_of_measurement: dBC
- type: peak
name: LCpeak_1min
id: LCpeak_1min
unit_of_measurement: dBC

# under dsp_filters section you can define multiple filters,
# which can be referenced later by each sensor

# for now only SOS filter type is supported, see math/filter-design.ipynb
# to learn how to create or convert other filter types to SOS
dsp_filters:
- id: f_inmp441 # INMP441 mic eq @ 48kHz
type: sos
coeffs:
# b0 b1 b2 a1 a2
- [1.0019784, -1.9908513, 0.9889158, -1.9951786, 0.99518436]
- id: f_a # A weighting @ 48kHz
type: sos
coeffs:
# b0 b1 b2 a1 a2
- [0.16999495, 0.741029, 0.52548885, -0.11321865, -0.056549273]
- [1., -2.00027, 1.0002706, -0.03433284, -0.79215795]
- [1., -0.709303, -0.29071867, -1.9822421, 0.9822986]
- id: f_c # C weighting @ 48kHz
type: sos
coeffs:
# b0 b1 b2 a1 a2
- [-0.49651518, -0.12296628, -0.0076134163, -0.37165618, 0.03453208]
- [1., 1.3294908, 0.44188643, 1.2312505, 0.37899444]
- [1., -2., 1., -1.9946145, 0.9946217]

sensors:
# 'eq' type sensor calculates Leq (average) sound level over specified period
- type: eq
name: LZeq_1s
id: LZeq_1s
# you can override updated_interval specified on top level
# individually per each sensor
update_interval: 1s

# you can have as many sensors of same type, but with different
# other parameters (e.g. update_interval) as needed
- type: eq
name: LZeq_1min
id: LZeq_1min
unit_of_measurement: dBZ

# 'max' sensor type calculates Lmax with specified window_size.
# for example, if update_interval is 60s and window_size is 1s
# then it will calculate 60 Leq values for each second of audio data
# and the result will be max of them
- type: max
name: LZmax_1s_1min
id: LZmax_1s_1min
window_size: 1s
unit_of_measurement: dBZ

# same as 'max', but 'min'
- type: min
name: LZmin_1s_1min
id: LZmin_1s_1min
window_size: 1s
unit_of_measurement: dBZ

# it finds max single sample over whole update_interval
- type: peak
name: LZpeak_1min
id: LZpeak_1min
unit_of_measurement: dBZ

- type: eq
name: LAeq_1min
id: LAeq_1min
unit_of_measurement: dBA

# The dsp_filters field is a list of filter IDs defined
# in the main component's corresponding section.
# If you're only using a single filter, you can omit the brackets.
# Alternatively, instead of referencing an existing filter,
# you can define a filter directly here in the same format
# as in the main component. However, this filter won't be reusable
# across other sensors, so it’s best to use this approach only when
# each sensor requires its own unique filters that don't overlap with others.
dsp_filters: [f_inmp441, f_a]
- type: max
name: LAmax_1s_1min
id: LAmax_1s_1min
window_size: 1s
unit_of_measurement: dBA
dsp_filters: [f_inmp441, f_a]
- type: min
name: LAmin_1s_1min
id: LAmin_1s_1min
window_size: 1s
unit_of_measurement: dBA
dsp_filters: [f_inmp441, f_a]
- type: peak
name: LApeak_1min
id: LApeak_1min
unit_of_measurement: dBA
dsp_filters: [f_inmp441, f_a]

- type: eq
name: LCeq_1min
id: LCeq_1min
unit_of_measurement: dBC
dsp_filters: [f_inmp441, f_c]
- type: max
name: LCmax_1s_1min
id: LCmax_1s_1min
window_size: 1s
unit_of_measurement: dBC
dsp_filters: [f_inmp441, f_c]
- type: min
name: LCmin_1s_1min
id: LCmin_1s_1min
window_size: 1s
unit_of_measurement: dBC
dsp_filters: [f_inmp441, f_c]
- type: peak
name: LCpeak_1min
id: LCpeak_1min
unit_of_measurement: dBC
dsp_filters: [f_inmp441, f_c]

# automation
# available actions:
Expand Down Expand Up @@ -253,13 +253,15 @@ Check out [filter-design notebook](math/filter-design.ipynb) to learn how those
## 10 bands spectrum analyzer
Although manually specifying IIR/SOS filters might not be the most user-friendly approach, it offers significant flexibility. This method lets you design and apply any filter you need, as long as you know how to tailor it to your requirements. Originally, my intention wasn’t to go beyond standard weighting functions like A/C, but I ended up experimenting with different filters. To showcase its capabilities, I created a 10-band spectrum analyzer using ten 6th-order filters, each targeting a specific frequency band - simply by writing the appropriate configuration file, without needing to modify the component's source code.
While manually specifying IIR/SOS filters might not be the most user-friendly approach, it offers considerable flexibility. This method lets you use any filter you need, as long as you know how to tailor it to your requirements. Originally, my intention wasn’t to go beyond standard weighting functions like A/C, however to showcase the capabilities, I created a 10-band spectrum analyzer using ten 6th-order filters, each targeting a specific frequency band - simply by writing the appropriate config file, without needing to modify the component's source code.
I set the `update_interval: 100ms` for real-time visualization, displaying the data as sliders using the web server’s number/slider component. While this is probably an abuse of the sliders and web server, since they may not be designed to handle such frequent updates, it does push the ESP32 to its limits, yet it still works. The sound meter component, with 10 x 6 = 60 SOS filters, uses about 60-70% of the CPU, and I assume the web server also consumes some CPU power to send approximately 100 messages per second. So, this is quite a CPU-intensive task, and you'll need to be cautious with it. I chose 6th-order filters somewhat arbitrarily; you could experiment with lower-order filters, which might meet your needs while using less CPU power.

I set the `update_interval: 100ms` to achieve real-time visualization, displaying the data as sliders using the web server’s number/slider component. While this is probably not the intended use of the sliders and web server, since they may not be designed to handle such frequent updates, it does push the ESP32 to its limits, yet it still works. The sound meter component, with 10 x 6 = 60 SOS filters, uses about 60-70% of the CPU, and I assume the web server also consumes some CPU power to send approximately 100 messages per second. So, this is quite a CPU-intensive task, and you'll need to be cautious with it. I chose 6th-order filters somewhat arbitrarily; you could experiment with lower-order filters, which might meet your needs while using less CPU power.
While this setup serves as a stress test, you could also use it to monitor different frequency bands over longer time intervals with less frequent updates. Alternatively, you could filter only specific frequencies - you don’t have to use all 10 bands - as you can design your own IIR filters based on your needs.

While this setup serves as a stress test for real-time updates, you could also use it to monitor different frequency bands over longer time intervals with less frequent updates. Alternatively, you could filter only specific frequencies - you don’t have to use all 10 bands - as you can design your own IIR filters based on your needs.
Here is the example config: [10-bands-spectrum-analyzer-example-config.yaml](configs/10-bands-spectrum-analyzer-example-config.yaml)

Here is an example config: [10-bands-spectrum-analyzer-example-config.yaml](configs/10-bands-spectrum-analyzer-example-config.yaml)
<img width="1189" src="https://github.com/user-attachments/assets/8a23774d-46f2-4162-8504-4e46bfe50a80">

## Performance

Expand Down
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Expand Up @@ -40,7 +40,7 @@
cv.Optional(CONF_DIN_PIN): pins.internal_gpio_input_pin_schema,
cv.Optional(CONF_DOUT_PIN): pins.internal_gpio_output_pin_schema,
cv.Optional(CONF_SAMPLE_RATE, 48000): cv.positive_not_null_int,
cv.Optional(CONF_BITS_PER_SAMPLE, 32): cv.one_of(8, 16, 24, 32, int=True),
cv.Optional(CONF_BITS_PER_SAMPLE, 16): cv.one_of(8, 16, 24, 32, int=True),
cv.Optional(CONF_DMA_BUF_COUNT, 8): cv.positive_not_null_int,
cv.Optional(CONF_DMA_BUF_LEN, 256): cv.positive_not_null_int,
cv.Optional(CONF_USE_APLL, False): cv.boolean,
Expand Down
6 changes: 2 additions & 4 deletions configs/10-bands-spectrum-analyzer-example-config.yaml
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Expand Up @@ -61,14 +61,13 @@ i2s:
bck_pin: 39
din_pin: 38
sample_rate: 48000
bits_per_sample: 32
bits_per_sample: 16
dma_buf_count: 8
dma_buf_len: 256
use_apll: true
bits_shift: 8
bits_shift: 0
channel: right

# yamllint disable rule:line-length
sound_level_meter:
id: slm
is_on: false
Expand Down Expand Up @@ -302,7 +301,6 @@ sound_level_meter:
- number.set:
id: number_band9
value: !lambda 'return std::isnan(x) ? 20 : x;'
# yamllint enable

number:
- platform: template
Expand Down
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