Difference between revisions of "DustSensor"

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== Introduction ==
 
== Introduction ==
To get an idea of the levels of fine dust around my house, I ordered some dust sensor modules to play around with.
+
[[File:stofradar.png|thumb|right|PM10 in the morning of 2018-06-03]]
 +
[[File:stofradar2.png|thumb|right|PM10 at around 2018-06-03 20:50 UTC]]
 +
To get an idea of the levels of atmospheric particulate matter around my house, I ordered some dust sensor modules to play around with.
 
In particular, I ordered these ones:
 
In particular, I ordered these ones:
 
* The [http://www.plantower.com/en/content/?110.html Plantower PMS 7003] ([https://nl.aliexpress.com/item/dit_is_m/32639894148.html AliExpress link]);
 
* The [http://www.plantower.com/en/content/?110.html Plantower PMS 7003] ([https://nl.aliexpress.com/item/dit_is_m/32639894148.html AliExpress link]);
 
* The SDS011 ([https://nl.aliexpress.com/item/aliexpress/32617788139.html AliExpress link]).
 
* The SDS011 ([https://nl.aliexpress.com/item/aliexpress/32617788139.html AliExpress link]).
 
The PMS7003 is being advertised as an advanced generation of dust sensor (7th generation), while still reasonably priced (E15,-).
 
The PMS7003 is being advertised as an advanced generation of dust sensor (7th generation), while still reasonably priced (E15,-).
They use a laser to perform the measurement and it contains a small fan to move the air around.
+
It uses a laser to perform the measurement and contains a small fan to move the air around.
  
In parallel with the fine dust level measurement, my device also measures basic meteo data using a BME280 module: temperature, relative humidity and air pressure.
+
In parallel with the atmospheric particulate matter level measurement, my device also measures basic meteo data using a BME280 module: temperature, relative humidity and air pressure.
  
 
I recommend to also get the PMS7003 cable converter board. The pitch of the connector on the sensor module is slightly non-standard: 2 x 5 pins with a spacing of 0.05 inch (instead of the common 0.1 inch spacing).  
 
I recommend to also get the PMS7003 cable converter board. The pitch of the connector on the sensor module is slightly non-standard: 2 x 5 pins with a spacing of 0.05 inch (instead of the common 0.1 inch spacing).  
  
 
The data produced by this sensor is sent as JSON to a MQTT server.
 
The data produced by this sensor is sent as JSON to a MQTT server.
From there it is picked up by two protocol converters:
+
From there it is picked up by a protocol converter:
1) the Telegraf plugin to insert it into my own influx db and
+
a [https://github.com/bertrik/dustsensorbridge custom written Java application] to forward it to the RIVM samenmeten website
2) a [https://github.com/bertrik/dustsensorbridge custom written Java application] to forward it to the RIVM samenmeten website
+
and forward it to luftdaten.info
  
 
=== Future work ===
 
=== Future work ===
  
 
Next steps:
 
Next steps:
* investigate whether it is possible to power the dust sensor off a solar panel (backup battery during the night), this would completely eliminate any wiring to the sensor
+
* build more luftdaten.info sensors and put them up in Gouda
* improve the casing such that the temperature reading is not influenced as much by direct solar irradiance
 
 
* build a luftdaten.info sensor and put it up at RevSpace
 
* build a luftdaten.info sensor and put it up at RevSpace
* for RIVM samenmeten: automatically determine geo position from wifi APs and the google/mozilla wifi location APIs
+
* investigate a LoRa version of the software + TTN forwarder so we can put up a sensor at Meteo Gouda (kinderboerderij).
* for RIVM samenmeten: use a scheme where the unique id is derived from the ESP id, this should make it very easy to add more sensors with minimal administrative overhead
+
* can we use Cayenne as a container to carry the dust sensor data over LoRa?
* create a LoRa version of the software + TTN forwarder so we can put up a sensor at Meteo Gouda (kinderboerderij).
 
  
 
== Results ==
 
== Results ==
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== Hardware ==
 
== Hardware ==
 +
 +
=== PMS7003 ===
 
[[File:dustsensor_window.jpg|thumb|right]]
 
[[File:dustsensor_window.jpg|thumb|right]]
  
Line 54: Line 56:
 
I connect it using a NodeMCU.
 
I connect it using a NodeMCU.
  
The module gives an estimate of the total mass of the particles (microgram/m3) in 3 categories: PM1.0, PM2.5 and PM10, both for "standard particle" (CF-1) and "standard atmosphere".
+
The module gives an estimate of the total mass of the particles (microgram/m3) in 3 categories: PM10, PM2.5 and PM1.0, both for "standard particle" (CF-1) and "standard atmosphere".
 
It also makes an estimate of the raw number of particles per size category, total 6 categories: 0.3-0.5-1.0-2.5-5.0-10 micrometer.
 
It also makes an estimate of the raw number of particles per size category, total 6 categories: 0.3-0.5-1.0-2.5-5.0-10 micrometer.
 
I don't know how it actually works on the inside and is able to make a distinction between particles of different size.
 
I don't know how it actually works on the inside and is able to make a distinction between particles of different size.
Line 65: Line 67:
 
!Remark
 
!Remark
 
|-
 
|-
|D3
+
|-
 
|PMS7003-RST
 
|PMS7003-RST
 
|Pulled-up to 3.3V on NodeMCU side, may not be actually needed
 
|Pulled-up to 3.3V on NodeMCU side, may not be actually needed
 
|-
 
|-
|D4
+
|-
 
|PMS7003-SET
 
|PMS7003-SET
 
|Pulled-up to 3.3V on NodeMCU side, may not be actually needed
 
|Pulled-up to 3.3V on NodeMCU side, may not be actually needed
 
|-
 
|-
|D5
+
|D1
|BME280-SCL
 
|I2C-SCL
 
|-
 
|D6
 
|BME280-SDA
 
|I2C-SDA,
 
|-
 
|D7
 
 
|PMS7003-TX
 
|PMS7003-TX
 
|NodeMCU receive, PMS7003 transmit
 
|NodeMCU receive, PMS7003 transmit
 
|-
 
|-
|D8
+
|D2
 
|PMS7003-RX
 
|PMS7003-RX
 
|NodeMCU transmit, PMS7003 receive
 
|NodeMCU transmit, PMS7003 receive
 +
|-
 +
|D3
 +
|BME280-SDA
 +
|I2C-SDA
 +
|-
 +
|D4
 +
|BME280-SCL
 +
|I2C-SCL
 
|-
 
|-
 
|GND
 
|GND
Line 103: Line 105:
  
 
Special thanks to [[User:Crashjuh|Crashjuh]] for helping with the cable, putting dupont connectors on them, making it a lot easier to connect the module to an ESP8266.
 
Special thanks to [[User:Crashjuh|Crashjuh]] for helping with the cable, putting dupont connectors on them, making it a lot easier to connect the module to an ESP8266.
 +
 +
=== SDS011 ===
 +
Datasheets:
 +
* [https://nettigo.pl/attachments/415 command protocol]
  
 
== Software ==
 
== Software ==
 
The software archive can be found at github, it consists of the following parts:
 
The software archive can be found at github, it consists of the following parts:
* [https://github.com/bertrik/sds011 esp arduino software for reading the sds011 dust sensor] and sending it as an MQTT stream;
+
* [https://github.com/bertrik/sds011 esp arduino software for reading the SDS011] and sending it as an MQTT stream;
* [https://github.com/bertrik/pms7003_esp arduino software reading the PMS7003] and sending it as an MQTT stream;
+
* [https://github.com/bertrik/pms7003_esp arduino software for reading the PMS7003] and sending it as an MQTT stream;
* [https://github.com/bertrik/sds011 arduino software reading the SDS011] and sending it as an MQTT stream;
 
 
* a Java based [https://github.com/bertrik/dustsensorbridge bridge application] that takes the MQTT data produced by the arduino and forwards it to other backends, like the RIVM influx database, luftdaten.info API.
 
* a Java based [https://github.com/bertrik/dustsensorbridge bridge application] that takes the MQTT data produced by the arduino and forwards it to other backends, like the RIVM influx database, luftdaten.info API.
  
Line 146: Line 151:
  
 
== References ==
 
== References ==
[https://keetweej.vanheusden.com/grafana/d/JUIM-ikmz/rivm-data?orgId=2 Grafana page of my sensor data].
+
Measurement data of this particular sensor:
 +
* [https://keetweej.vanheusden.com/grafana/d/JUIM-ikmz/rivm-data?orgId=2 Grafana page of my sensor data].
 +
* [https://www.madavi.de/sensor/graph.php?sensor=esp8266-9137604-pms particulate matter graphs] at madavi
 +
* [https://www.madavi.de/sensor/graph.php?sensor=esp8266-9137604-bme280 humidity and pressure graphs] at madavi
  
[http://aqicn.org/sensor/pms5003-7003/ Page on aqicn about the PMS5003/7003]
+
Overview of dust sensor types and comparisons between them:
 
+
* [http://aqicn.org/sensor/pms5003-7003/ Page on aqicn about the PMS5003/7003]
List of dust sensors:
 
 
* list of sensors [https://www.samenmetenaanluchtkwaliteit.nl/sensoren-voor-fijn-stof-pm25pm10 from "samen meten aan luchtkwaliteit"].
 
* list of sensors [https://www.samenmetenaanluchtkwaliteit.nl/sensoren-voor-fijn-stof-pm25pm10 from "samen meten aan luchtkwaliteit"].
 
* another [http://aqicn.org/sensor/ overview of dust sensors].
 
* another [http://aqicn.org/sensor/ overview of dust sensors].
Line 164: Line 171:
 
* [https://scapeler.wordpress.com/ scapeler]
 
* [https://scapeler.wordpress.com/ scapeler]
  
== Making graphs of dust data ==
+
== Visualizing dust data ==
To create nice graphs, I used the following stack of tools/applications:
+
See also my [[Stofradar]] page.
 +
 
 +
=== Grafana ===
 +
To create nice graphs in Grafana, I used the following stack of tools/applications:
 
* a dust sensor, as described here, that publishes measurement data towards an MQTT server
 
* a dust sensor, as described here, that publishes measurement data towards an MQTT server
 
* an MQTT server to accept the data and forward it to subscribers
 
* an MQTT server to accept the data and forward it to subscribers
Line 172: Line 182:
 
* grafana, to grab the data from the database and display it
 
* grafana, to grab the data from the database and display it
  
=== Sensor ===
+
==== Sensor ====
 
The sensor produces JSON, grouping the information from one message from the module together. Example
 
The sensor produces JSON, grouping the information from one message from the module together. Example
   bertrik/pms7003/json {"pms7003":{"pm1_0":2,"pm2_5":3,"pm10":4},"bme280":{"t":21.1,"rh":50,"p":1012.4}}
+
   bertrik/pms7003/json {"alive":1138,"pms7003":{"pm1_0":2,"pm2_5":3,"pm10":4},"bme280":{"t":21.1,"rh":50,"p":1012.4}}
  
=== Telegraf ===
+
==== Telegraf ====
 
Things I did:
 
Things I did:
 
* downloaded and installed the Telegraf .deb from [https://github.com/influxdata/telegraf here].
 
* downloaded and installed the Telegraf .deb from [https://github.com/influxdata/telegraf here].
Line 192: Line 202:
 
   systemctl restart telegraf
 
   systemctl restart telegraf
  
=== Grafana ===
+
==== Grafana ====
 
Add a data source, pointing to the influx DB. Provide credentials and verify by pressing the 'test connection' button.
 
Add a data source, pointing to the influx DB. Provide credentials and verify by pressing the 'test connection' button.
  
Line 224: Line 234:
  
 
Luftdaten.info have a [http://luftdaten.info/feinstaubsensor-bauen/ pretty good description] of how to build your own sensor for their network.
 
Luftdaten.info have a [http://luftdaten.info/feinstaubsensor-bauen/ pretty good description] of how to build your own sensor for their network.
They're keeping it simple, just wire an sds011 dust sensor with up with some du-pont cable to a nodemcu and put it in a plastic enclosure anyone can build using some drain water piping.
+
They're keeping it simple, just wire an sds011 dust sensor with some du-pont cable to a nodemcu and put it in a plastic enclosure anyone can build using some drain water piping.
  
 
It appears hack42 is [https://hack42.nl/wiki/FijnstofMeten also considering to join the luftdaten.info network].  
 
It appears hack42 is [https://hack42.nl/wiki/FijnstofMeten also considering to join the luftdaten.info network].  
Line 248: Line 258:
 
** "software_version": string containing the software version of the sender, for example "python-dusty 0.0.1"
 
** "software_version": string containing the software version of the sender, for example "python-dusty 0.0.1"
 
** "sensordatavalues": array of structures containing measurement data, looking like this:
 
** "sensordatavalues": array of structures containing measurement data, looking like this:
*** "value_type" (when X-PIN=1): string describing the measurement item type, can be "P1" (PM10 value) or "P2" (PM2.5 value) with dust value in ug/m3 I suppose
+
*** "value_type" (when X-PIN=1): string describing the measurement item type, can be "P1" (PM10 value) or "P2" (PM2.5 value) with dust value in ug/m3. It appears there is also an unofficial "P0" field which encodes for the PM1.0 value.
 
*** "value_type" (when X-PIN=7): string describing the measurement item type, can be "temperature", "humidity"
 
*** "value_type" (when X-PIN=7): string describing the measurement item type, can be "temperature", "humidity"
 
*** "value_type" (when X-PIN=11): string describing the measurement item type, can be "temperature", "pressure", "humidity"
 
*** "value_type" (when X-PIN=11): string describing the measurement item type, can be "temperature", "pressure", "humidity"
Line 255: Line 265:
 
Other meta-information like latitude/longitude of the sensor is sent by an e-mail registration process.
 
Other meta-information like latitude/longitude of the sensor is sent by an e-mail registration process.
 
This is linked to your measurements by means of the unique sensor id.
 
This is linked to your measurements by means of the unique sensor id.
 +
 +
== Revspace particulate matter sensor ==
 +
The idea is to put up a particulate matter sensor up at RevSpace and register it with luftdaten, so it can be used in the luftdaten and RIVM samenmeten citizen-science projects.
 +
 +
Things preventing completion of this sub-project:
 +
* it is not clear whether we can actually put up the proposed PM sensor enclosure (too ugly or something, who decides this?)
 +
* I (bertrik) no longer have notes of who helps to fund a RevSpace particulate matter sensor
 +
 +
Access it locally as http://ESP_B74C71/ ?
 +
Feinstaubsensor-12012657
 +
 +
Madavi data:
 +
* Particulate matter: https://www.madavi.de/sensor/graph.php?sensor=esp8266-12012657-sds011
 +
* Temperature / humidity / pressure: https://www.madavi.de/sensor/graph.php?sensor=esp8266-12012657-bme280

Revision as of 22:57, 24 December 2018

Project Dust Sensor
Pms7003.jpg
Experiments with a dust sensor
Status Completed
Contact bertrik
Last Update 2018-12-24

Introduction

PM10 in the morning of 2018-06-03
PM10 at around 2018-06-03 20:50 UTC

To get an idea of the levels of atmospheric particulate matter around my house, I ordered some dust sensor modules to play around with. In particular, I ordered these ones:

The PMS7003 is being advertised as an advanced generation of dust sensor (7th generation), while still reasonably priced (E15,-). It uses a laser to perform the measurement and contains a small fan to move the air around.

In parallel with the atmospheric particulate matter level measurement, my device also measures basic meteo data using a BME280 module: temperature, relative humidity and air pressure.

I recommend to also get the PMS7003 cable converter board. The pitch of the connector on the sensor module is slightly non-standard: 2 x 5 pins with a spacing of 0.05 inch (instead of the common 0.1 inch spacing).

The data produced by this sensor is sent as JSON to a MQTT server. From there it is picked up by a protocol converter: a custom written Java application to forward it to the RIVM samenmeten website and forward it to luftdaten.info

Future work

Next steps:

  • build more luftdaten.info sensors and put them up in Gouda
  • build a luftdaten.info sensor and put it up at RevSpace
  • investigate a LoRa version of the software + TTN forwarder so we can put up a sensor at Meteo Gouda (kinderboerderij).
  • can we use Cayenne as a container to carry the dust sensor data over LoRa?

Results

Below is a graph of the dust levels around new years eve 2017/2018, separated by particle size

Dust 2017 2018.png

You can clearly see a peak just after midnight.

See also the map of these two experiments:

Hardware

PMS7003

Dustsensor window.jpg

PMS7003 data sheets can be found:

The PMS7003 takes 5V to run and communicates using 3.3V levels. I connect it using a NodeMCU.

The module gives an estimate of the total mass of the particles (microgram/m3) in 3 categories: PM10, PM2.5 and PM1.0, both for "standard particle" (CF-1) and "standard atmosphere". It also makes an estimate of the raw number of particles per size category, total 6 categories: 0.3-0.5-1.0-2.5-5.0-10 micrometer. I don't know how it actually works on the inside and is able to make a distinction between particles of different size.

Connections
NodeMCU PMS7003/BME280 Remark
PMS7003-RST Pulled-up to 3.3V on NodeMCU side, may not be actually needed
PMS7003-SET Pulled-up to 3.3V on NodeMCU side, may not be actually needed
D1 PMS7003-TX NodeMCU receive, PMS7003 transmit
D2 PMS7003-RX NodeMCU transmit, PMS7003 receive
D3 BME280-SDA I2C-SDA
D4 BME280-SCL I2C-SCL
GND PMS7003-GND / BME280-GND GND ground reference
VU PMS7003-VCC USB voltage (5V)
3.3V BME280-VCC

Special thanks to Crashjuh for helping with the cable, putting dupont connectors on them, making it a lot easier to connect the module to an ESP8266.

SDS011

Datasheets:

Software

The software archive can be found at github, it consists of the following parts:

Dust sensor

The dust sensor software is written for the Arduino environment.

Typing 'make' builds and runs unit tests that verify parsing of measurement data and construction of command data. The sub-directory 'pms7003_esp' contains the .ino file to be opened in the Arduino IDE.

Libraries used:

  • SoftwareSerial (built-in) for serial communication with the sensor
  • WiFiClient (built-in) for WiFi connectivity
  • WiFiManager (tzapu) to present a captive portal and allow selection of an AP to connect to the internet
  • PubSubClient (Nick O'Leary) to handle publishing of data over MQTT
  • BME280I2C (Tyler Glenn) and wire for interacting with a BME280 for basic meteo data (temperature, humidity, pressure)

The Arduino software has platformio.org configuration files, so if you're using that, you can just build it with

 pio run

PMS7003

Reading measurements from the pms7003 works, sending commands to the module does not. I don't know yet whether this is a hardware or software problem.

Typing 'make' builds and runs unit tests that verify parsing of measurement data and construction of command data. The sub-directory 'pms7003_esp' contains the .ino file to be opened in the Arduino IDE.

SDS011

Typing 'make' builds and runs unit tests that verify parsing of measurement data and construction of command data. The sub-directory 'sds011_esp' contains the .ino file to be opened in the Arduino IDE.

Infrastructure

The idea is that the dust sensor send its data to an MQTT server. From there on, there is an application written in Java that picks up the data from MQTT and redistributes it to other backends, like samenmeten.rivm.nl and luftdaten.info.

The topic that the sensor publishes on is

 bertrik/dust/<sensorid>

where sensorid is the id of the ESP8266, in hexadecimal format, e.g. AB12CD

References

Measurement data of this particular sensor:

Overview of dust sensor types and comparisons between them:

Citizen science projects for measuring airborne dust:

Dust measurement blog:

Visualizing dust data

See also my Stofradar page.

Grafana

To create nice graphs in Grafana, I used the following stack of tools/applications:

  • a dust sensor, as described here, that publishes measurement data towards an MQTT server
  • an MQTT server to accept the data and forward it to subscribers
  • the 'Telegraf' importer that listens on the MQTT stream and converts the data to influx database
  • an influx database, to store the measurement data
  • grafana, to grab the data from the database and display it

Sensor

The sensor produces JSON, grouping the information from one message from the module together. Example

  bertrik/pms7003/json {"alive":1138,"pms7003":{"pm1_0":2,"pm2_5":3,"pm10":4},"bme280":{"t":21.1,"rh":50,"p":1012.4}}

Telegraf

Things I did:

  • downloaded and installed the Telegraf .deb from here.
  • generated a default configuration using:
  telegraf --input-filter mqtt_consumer --output-filter influxdb config >telegraf.conf
  • edited the configuration to set mqtt and influxdb settings
    • influxdb output plugin
    • mqtt_consumer plugin
      • topics=[ "bertrik/pms7003/json" ]
      • data_format="json"
      • data_type="integer"
  • test-run using 'telegraf <TODO>'
  • copied the final telegraf.conf to /etc/telegraf and restarted the telegraf service
  systemctl restart telegraf

Grafana

Add a data source, pointing to the influx DB. Provide credentials and verify by pressing the 'test connection' button.

Add a dashboard, add a row to the dashboard, add a graph panel to the row. Under 'metrics', add a query with the following properties:

  • FROM mqtt_consumer WHERE topic = bertrik/pms7003/json
  • SELECT field(amb_pm10)
  • GROUP BY
  • ALIAS BY PM10
  • repeat for other particle sizes (amb_pm2_5 and amb_pm_1_0)

Regelgeving

From: https://www.rivm.nl/Documenten_en_publicaties/Algemeen_Actueel/Uitgaven/Milieu_Leefomgeving/Dossier_Fijn_stof/Maart_2013/Regelgeving.pdf

 Regelgeving voor fijn stof (PM10)
 De regelgeving voor fijn stof (PM10) kent twee doelstellingen:
 - Een grenswaarde voor het jaargemiddelde: 40 µg/m3 als jaargemiddelde mag niet worden
   overschreden. Aan deze grenswaarde moet sinds 2005 worden voldaan. Behoudens
   ‘derogatie’ zijn geen uitzonderingen mogelijk (->Derogatie). Deze grenswaarde beoogt
   vooral bescherming te bieden tegen de langetermijneffecten van fijn stof.
 - Een grenswaarde voor het daggemiddelde: 50 µg/m3 als daggemiddelde mag op niet meer
   dan 35 dagen per jaar worden overschreden. 5 Aan deze grenswaarde moet sinds 2005
   worden voldaan. Behoudens ‘derogatie’ zijn geen uitzonderingen mogelijk (->Derogatie).
   Deze grenswaarde is vooral bedoeld om bescherming te bieden tegen de
   kortetermijneffecten van fijn stof.

Luftdaten.info

I'm forwarding my data also to the luftdaten.info website so it appears on the lufdaten.info map. I use the same kind of mechanism as used for RIVM: write a Java program to capture the MQTT stream and convert it to their API.

Luftdaten.info have a pretty good description of how to build your own sensor for their network. They're keeping it simple, just wire an sds011 dust sensor with some du-pont cable to a nodemcu and put it in a plastic enclosure anyone can build using some drain water piping.

It appears hack42 is also considering to join the luftdaten.info network.

protocol

Most of the Luftdaten.info upload protocols are described on the luftdaten wiki.

Some examples of how to use it, can be found here: here and this code from ttn-ulm-muecke.

  • data is sent as a HTTP POST to https://api.luftdaten.info/v1/push-sensor-data/ (NOTE: the trailing slash!)
  • the HTTP POST uses headers "X-Pin" and "X-Sensor" (not case-sensitive it appears)
    • header "X-Pin" indicates the type of data
      • 1 = SDS011 or PMS7003
      • 3 = BMP180
      • 5 = PPD42NS
      • 7 = DHT22
      • 11 = BME280
    • header "X-Sensor" indicates the unique sensor id, for example "esp8266-9137604"
    • header "Content-Type" with value "application/json" (NOTE: API describes this header, but it's not explicitly sent by the implementations above)
  • the body of the POST is JSON with the following fields:
    • "software_version": string containing the software version of the sender, for example "python-dusty 0.0.1"
    • "sensordatavalues": array of structures containing measurement data, looking like this:
      • "value_type" (when X-PIN=1): string describing the measurement item type, can be "P1" (PM10 value) or "P2" (PM2.5 value) with dust value in ug/m3. It appears there is also an unofficial "P0" field which encodes for the PM1.0 value.
      • "value_type" (when X-PIN=7): string describing the measurement item type, can be "temperature", "humidity"
      • "value_type" (when X-PIN=11): string describing the measurement item type, can be "temperature", "pressure", "humidity"
      • "value": field containing the measurement value (NOTE: in string quotes, not as numeric values!)

Other meta-information like latitude/longitude of the sensor is sent by an e-mail registration process. This is linked to your measurements by means of the unique sensor id.

Revspace particulate matter sensor

The idea is to put up a particulate matter sensor up at RevSpace and register it with luftdaten, so it can be used in the luftdaten and RIVM samenmeten citizen-science projects.

Things preventing completion of this sub-project:

  • it is not clear whether we can actually put up the proposed PM sensor enclosure (too ugly or something, who decides this?)
  • I (bertrik) no longer have notes of who helps to fund a RevSpace particulate matter sensor

Access it locally as http://ESP_B74C71/ ? Feinstaubsensor-12012657

Madavi data: