Suitable for: <\/strong>advanced<\/p>\n\n Time required:<\/strong> at least 2 h<\/p>\n\n What you need:<\/strong> Raspberry Pi<\/a> (model 2 or newer recommended), sensors or other interesting data sources<\/p>\n\n <\/p>\n\n InfluxDB is a Time Series Database (TSDB), a database which was developed especially for time series. Compared to conventional databases such as mySQL, TSDBs have several advantages:<\/p>\n\n InfluxDB also includes the program Telegraf, which collects measured values from many sources and forwards them to InfluxDB. In this tutorial Telegraf is used to collect data like the CPU usage of the Raspberry Pis. If this is not desired, the installation of Telegraf is not necessary.<\/p>\n\n Grafana is a platform for the visualization of time series. Data can be presented e.g. with graphs, tables and heat maps. A large selection of plugins offers many possibilities for extension. If you want to have a look at the interface before installation, you can use the live demo on https:\/\/play.grafana.org<\/a>.<\/p>\n\n Due to the higher write load on the SD card caused by the database, it is recommended to install the operating system on a better data carrier, for example a USB-SSD. The installation of Raspbian will not be discussed further at this point, the tutorial is based on the version “Raspbian Buster Lite”.<\/p>\n\n The packages in the official Raspbian repositories are outdated, so the repositories of the respective developers must be added:<\/p>\n\n By default Grafana starts a web server on port 3000, so the frontend can be reached with the browser under the URL http:\/\/:3000. The login is “admin”\/”admin” and should be changed directly at the first login. After that the home dashboard is already displayed.<\/p>\n\n First Grafana must be connected to InfluxDB. For this purpose, a new data source is created by clicking on “Add Data Source”, in the selection afterwards “InfluxDB” must be selected. Most of the settings can be left at the default values at first, only the URL has to be entered: http:\/\/localhost:8086. In addition, the database ‘telegraf’ has to be entered under “InfluxDB Details”. A click on “Save & Test” saves the settings, the confirmation “Data source is working” should appear.<\/p>\n\n After that you can already create the first dashboard, this is done by clicking the “New Dashboard” button on the home dashboard. The first panel has already been created automatically, click “Add Query” to get to the panel menu.<\/p>\n\n Telegraf should already have collected some data about the Raspberry Pi since the installation, like CPU load, RAM usage etc. To display the CPU load, for example, the measurement series “cpu” must be selected in the “FROM” line under “select measurement”. Afterwards, the field “usage_system” or “usage_user” can be selected in the line “SELECT” under “value”.<\/p>\n\n Once the data has been selected, the buttons on the left are used to access further menus in which the graphical display can be configured.<\/p>\n\n Telegraf has a multitude of “Input Plugins”, which enable the collection of various data. Most plugins are designed for servers and measure statistics about different server applications. A funny exception to this is the ‘minecraft’ plugin, which collects the scoreboards of players of a Minecraft server. A detailed list is available in the Telegraf source code<\/a>. To enable plugins, the configuration file ‘\/etc\/telegraf\/telegraf.conf’ must be modified. If you want to get deeper into Telegraf, please refer to the documentation<\/a>.<\/p>\n\n InfluxDB accepts data in the form of HTTP requests, so all network-compatible devices can easily send measured values to the database. Here, ‘curl’ is used as an example for a sensor:<\/p>\n\n This query stores a measured value in the measurement series ‘sensor’, with the additional marking ‘location=kitchen’ and the field ‘temperature’, with the value ‘24.7’. This measured value appears immediately in Grafana after setting up a dashboard.<\/p>\n\n In order to connect smaller sensors to the database, they must be sent to the database by a microcontroller. The easiest way to do this is with the ESP8266 and ESP32 controllers from Espressif, as these can communicate directly with the Raspberry via WLAN. There is also a suitable Arduino library<\/a>, so the same measured value can be transmitted in a few lines of code:<\/p>\n\n A big disadvantage of these two controllers is the high current consumption due to the WLAN connection (about 80mA at 3.3V). For battery operation it is therefore absolutely necessary to use the sleep modes. Furthermore, the range is limited by the range of the WLAN network.<\/p>\n\n The best solution for power consumption and range is the relatively new wireless protocol LoRa (Long Range). A similar sensor with a LoRa transmitter has been tirelessly measuring the temperature in the author’s garden (with two mignon cells and every minute) for almost a year now and was able to successfully transmit data over several kilometers in range tests. However, LoRa requires special transmitters and receivers, the setup of which will be explained in upcoming How-To’s.<\/p>\n\n The article showed how a Raspberry Pi with InfluxDB and Grafana can be used to collect data from sensors and present it in an appealing way. Such a setup has been used by the author for about two years. Here are some interesting applications, which have all been integrated into the system:<\/p>\n\n <\/p>\n","protected":false},"excerpt":{"rendered":" Anyone who wants to record sensor data over a long period of time is inevitably faced with a problem: How can the collected data be stored and presented?InfluxDB and Grafana are actually tools designed for monitoring large servers, networks and websites. This tutorial explains how this combination can be used to visualize sensor data at […]<\/p>\n","protected":false},"author":1,"featured_media":41532,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6037],"tags":[],"class_list":["post-40575","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-projects"],"yoast_head":"\nThe Tools<\/strong><\/h2>\n\n
InfluxDB<\/strong><\/h3>\n\n
Grafana<\/strong><\/h3>\n\n
Setup on the Raspberry Pi<\/strong><\/h2>\n\n
At the very least, an SD card designed for high write load should be used (for example, a card for Dashcams).<\/p>\n\nInstalling the packages<\/h3>\n\n
```bash\ncurl -sL https:\/\/packages.grafana.com\/gpg.key | sudo apt-key add -\ncurl -sL https:\/\/repos.influxdata.com\/influxdb.key | sudo apt-key add -\n\necho \"deb https:\/\/repos.influxdata.com\/debian stretch stable\" | sudo tee \/etc\/apt\/sources.list.d\/influxdb.list\necho \"deb stable main\" | sudo tee \/etc\/apt\/sources.list.d\/grafana.list\n\nsudo apt-get update\nsudo apt-get install -y grafana influxdb telegraf\n\nsudo systemctl enable influxdb grafana-server telegraf\nsudo systemctl start influxdb grafana-server telegraf\n```<\/code><\/pre>\n\nConfiguration<\/strong><\/h3>\n\n
![\"Home](\"https:\/\/www.reichelt.com\/magazin\/wp-content\/uploads\/2020\/03\/home_dashboard.png\")
<\/a><\/figure>\nDashboards<\/strong><\/h3>\n\n
![\"First](\"https:\/\/www.reichelt.com\/magazin\/wp-content\/uploads\/2020\/03\/first_panel.png\")
<\/a><\/figure>\nAdditional data sources in Telegraf<\/strong><\/h3>\n\n
Integration of sensor data<\/strong><\/h2>\n\n
Data format<\/strong><\/h3>\n\n
```bash\ncurl -i -XPOST 'http:\/\/<IP-des-Pis>:8086\/write?db=mydb' --data-binary 'sensor,ort=kueche temperatur=24.7'\n```<\/code><\/pre>\n\nESP8266 \/ ESP32<\/strong><\/h3>\n\n
```c++\nInfluxData measurement(\"sensor\");\nmeasurement.addTag(\"ort\", \"kueche\");\nmeasurement.addValue(\"temperatur\", 24.7);\n\ninflux.write(measurement);\n```<\/code><\/pre>\n\nLoRaWAN<\/strong><\/h3>\n\n
![\"Sensor](\"https:\/\/www.reichelt.com\/magazin\/wp-content\/uploads\/2020\/03\/sensor_outside.png\")
<\/a><\/figure>\nFurther possibilities<\/strong><\/h2>\n\n
![\"Wetter\"](\"https:\/\/www.reichelt.com\/magazin\/wp-content\/uploads\/2020\/03\/weather-1024x501.png\")
<\/a><\/figure><\/li>![\"Elektrizität\"](\"https:\/\/www.reichelt.com\/magazin\/wp-content\/uploads\/2020\/03\/electricity-1024x500.png\")
<\/a><\/figure><\/li><\/ul><\/figure>\n
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