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https://github.com/zonque/gas-tally

ESP8266 based gas meter monitor
https://github.com/zonque/gas-tally

energy-monitor esp8266 gas-sensor iot magnetometer

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ESP8266 based gas meter monitor

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README 

        
# Gas Tally



A little project to keep track of gas usage and log it to [InfluxDB](https://www.influxdata.com/) for vizualisation.



It's built with a D1 mini board, featuring an ESP8266 and an HMC5883 magnet sensor chip, connected via I2C.



## Monitoring



Gas meters such as the the one pictured below have a small magnet in the last (rightmost) ring which

can be detected using a magnet sensor.



![meter](https://raw.githubusercontent.com/zonque/gas-tally/main/images/meter.jpg)



## Hardware wiring



A D1 mini module (ESP8266 based) was used and connected to an HMC5883 breakout board. Other ESP8266 derivates might also work.

Connect the I2C lines (SDA and SCL) and supply the HMC5883 board with +3.3v and GND. The DRDY pin can be left unconnected.



![wiring schematics](https://github.com/zonque/gas-tally/blob/main/images/wiring.png)



The sensor is then mounted underneath the gas meter. Duct tape is your friend :)



![installed](https://github.com/zonque/gas-tally/blob/main/images/installed.jpg)



## Firmware details



The firmware will do the following upon startup:



* Initialize the HMC5883

* Connect to the configured Wifi

* Set the local time using NTP

* Connect to InfluxDB



It will then periodically (once per second) read out the sensor values and print them to the serial console.



The Z axis of the magnet sensor is further evaluated, assuming that the sensor is mounted flat on the bottom of the gas meter.



For the purposes of debouncing, its value will have to drop below the configured `MAGNET_THRESHOLD_LOW` value,

and then rise above `MAGNET_THRESHOLD_HIGH` again.



This event signifies a full turnaround of the measured ring. A data point is now logged to InfluxDB with a fixed value as

configured in `DATA_POINT_VALUE`.



## Compiling



You will need to have [PlatformIO](https://platformio.org/) set up in order to satisfy the dependency libraries and compile the firmware.



Copy `include/config.h.template` to `include/config.h` and add your configuration to the variables documented in that file.



## Influx



The easiest way to get started is to use [InfluxDB's hosted cloud service](https://cloud2.influxdata.com/signup).



Use InfluxDB queries to make use of the data. Note that the data represents multiple data points with the same value each,

so you need to select the `sum` aggregation to plot meaningful graphs.



For instance, use the following query:



```

from(bucket: "gas-tally")

  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)

  |> filter(fn: (r) => r["_measurement"] == "usage")

  |> filter(fn: (r) => r["_field"] == "m3")

  |> filter(fn: (r) => r["sensor-id"] == "sensor-1")

  |> aggregateWindow(every: 5m, fn: sum, createEmpty: true)

  |> yield(name: "sum")

```



Here's an example of the plot that resulted from the query above:



![influx graph example](https://github.com/zonque/gas-tally/blob/main/images/influx.png)



## Homeassistant



[HomeAssistant](https://home-assistant.io) as support for Influx queries built-in. Here's an example config to display the measurements of your meter for the last hour, day and week:



```

- platform: influxdb

  api_version: 2

  ssl: true

  host: XXX

  port: 443

  token: XXX

  organization: XXX

  bucket: gas-tally

  queries_flux:

    - range_start: -7d

      name: Gas usage in the last 7 days

      query: >

        filter(fn: (r) => r["_measurement"] == "usage")

        |> filter(fn: (r) => r["sensor-id"] == "my-sensor")

        |> filter(fn: (r) => r["_field"] == "m3")

        |> aggregateWindow(every: inf, fn: sum)

        |> cumulativeSum()

      value_template: "{{ value|float(0)|round(2) }} m^3"

    - range_start: -24h

      name: Gas usage in the last 24h

      query: >

        filter(fn: (r) => r["_measurement"] == "usage")

        |> filter(fn: (r) => r["sensor-id"] == "my-sensor")

        |> filter(fn: (r) => r["_field"] == "m3")

        |> aggregateWindow(every: inf, fn: sum)

        |> cumulativeSum()

      value_template: "{{ value|float(0)|round(2) }} m^3"

    - range_start: -1h

      name: Gas usage in the last hour

      query: >

        filter(fn: (r) => r["_measurement"] == "usage")

        |> filter(fn: (r) => r["sensor-id"] == "my-sensor")

        |> filter(fn: (r) => r["_field"] == "m3")

        |> aggregateWindow(every: inf, fn: sum)

        |> cumulativeSum()

      value_template: "{{ value|float(0)|round(2) }} m^3"

```



## License



MIT