Pushing sensor data (temperature & humidity) to ThingsBoard and to Elasticsearch

This (sample) project does 2 things:

• Pushes sensor data (DHT11 - temperature & humidity) to ThingsBoard
• Queries ThingsBoard regularly (via Cron job) to update an Elasticsearch index for data visualization using Kibana & Timelion

Setup

Requirements

• Raspberry Pi 3
• DHT11 Temperature & Humidity sensor
• ThingsBoard deployment (local or cloud)
• Elasticsearch and Kibana (local or cloud)

Steps

ThingsBoard

• Log into your ThingsBoard environment
• Go to "Devices" and click "+"
• Name your device (e.g.: DHT11-device1)
• Once the device is created, go to Manage Credentials and copy the Access Token

Elasticsearch

• Create an Elasticsearch index using the schema provided in ES_schema.json

Raspberri Pi

• Connect the DHT11 to your Raspberry Pi 3

  DHT11 Data -> Raspberry PI GPIO 2
  DHT11 VCC -> Raspberry Pi 5V
  DHT11 GND -> Raspberry Pi GND

• clone this repository to your Raspberry Pi 3

  git clone https://github.com/gforce81/ThingsBoard-IoT.git

• install MQTT

  sudo pip install paho-mqtt

• update all the -config.json files to match your environments
• clone the Adafruit repository for the DHT11

  git clone https://github.com/adafruit/Adafruit_Python_DHT.git
  cd Adafruit_Python_DHT
  sudo python setup.py install

• Add the commands included in the cron_job.tx file to your Crontab
• Reload Cron:

 sudo service cron reload

• Start the telemetry gathering

 python mqtt-dht11.py

Dashboarding

• Head over to your Kibana instance
• Select Timelion
• Use the following query

 .es(index=thingsboard, timefield=temperatureTimestamp, metric=avg:temperature)
    .color(#ff0000)
    .points(radius=6, fill=1, fillColor=#009900)