RaspberryPi with DHT22 Sensor for Humidity and Temperature Data with InfluxDB
By Fahad Ahammed
- 8 minutes read - 1628 wordsI have been playing with RaspberryPI for a while. There are several project I tried to do with RaspberryPI. These boards play a significant role in my home lab for different experiments like Docker Private Repository, Media Server, Ad Blocker with pi-hole, Secure Proxy for anonymity, secure network access with VPN, Home Security Camera/Surveillance, Data Collector or scraper etc. But This time, I did buy a “DHT-22” sensor for monitoring room temperature and humidity. Humidity is my main concern and wanted to see how it fluctuates.
So, my main plan was to get a DHT-22 to connect properly
with my spare RapberryPI 3B+. I did order the sensor and 3 male-to-male jumper for connectivity. Though I should have had a BreadBoard too. However, raspberryPI had already Ubuntu Server 20 installed.
For DHT-22, I needed to connect the female-to-female into the pins
14: Ground
17: 3v3 Power
18: GPIO 24
This GPIO-24 was important to note down as it was needed in Python Code to access the sensor through this pin.
Yes, I have used python to access the sensor. For testing, I have used this code:
#!/usr/bin/python3
import Adafruit_DHT
import datetime
def th_reader():
# for DHT11
# sensor = 11
# for DHT22
sensor = 22
gpio = 24
h_t = Adafruit_DHT.read_retry(sensor, gpio)
humidity = h_t[0]
temperature = h_t[1]
if humidity is not None and temperature is not None:
temp = '{0:0.1f}°C'.format(temperature)
humid = '{0:0.1f}%'.format(humidity)
return {
"temperature": temp,
"humidity": humid
}
else:
temp = None
humid = None
return {
"temperature": temp,
"humidity": humid
}
if __name__ == '__main__':
print(th_reader())
The output it gives-
{
'temperature': '26.1°C',
'humidity': '85.8%'
}
But the requirements to run the code is-
sudo apt-get update
sudo apt-get install python3-pip
sudo python3 -m pip install --upgrade pip setuptools wheel
sudo pip3 install Adafruit_DHT
You can check other methods to install from here: https://github.com/adafruit/Adafruit_Python_DHT
This was enough for me. I wanted to run the script every 5 minutes through cron and store the data to already running influxDB instance in another RaspberryPI at which I can create dashboards and others. You can check how I am using InfluxDB through here: https://fahadahammed.com/explore-influxdb-part-1/
So, I did create a bucket in the influxDB and modified the code to this-
#!/usr/bin/python3
import Adafruit_DHT
import datetime
import threading
from influxdb_client import InfluxDBClient, Point, WritePrecision
from influxdb_client.client.write_api import SYNCHRONOUS
def th_reader():
# for DHT11
# sensor = 11
# for DHT22
sensor = 22
gpio = 24
h_t = Adafruit_DHT.read_retry(sensor, gpio)
humidity = h_t[0]
temperature = h_t[1]
if humidity is not None and temperature is not None:
temp = '{0:0.1f}°C'.format(temperature)
humid = '{0:0.1f}%'.format(humidity)
return {
"temperature": temperature,
"humidity": humidity
}
else:
temp = None
humid = None
return {
"temperature": temp,
"humidity": humid
}
def write_to_influxdb(data_to_write):
# You can generate an API token from the "API Tokens Tab" in the UI
token = "<INFLUX_TOKEN>"
org = "myorg"
bucket = "dht"
influx_url = "<INFLUX_URL>"
with InfluxDBClient(url=influx_url, token=token, org=org) as client:
write_api = client.write_api(write_options=SYNCHRONOUS)
pt = Point("temperature").tag("host", "pi").field("temperature", int(data_to_write.get("temperature"))).time(datetime.datetime.utcnow(), WritePrecision.NS)
write_api.write(bucket, org, pt)
client.close()
with InfluxDBClient(url=influx_url, token=token, org=org) as client:
write_api = client.write_api(write_options=SYNCHRONOUS)
ph = Point("humidity").tag("host", "pi").field("humidity", data_to_write.get("humidity")).time(datetime.datetime.utcnow(), WritePrecision.NS)
write_api.write(bucket, org, ph)
client.close()
return True
if __name__ == '__main__':
th_data = th_reader()
print(th_data)
# write_to_influxdb(data_to_write=th_data)
t1 = threading.Thread(target=write_to_influxdb, kwargs={"data_to_write": th_data})
t1.start()
If you want to use the code block, please do replace the <INFLUX_URL> and <INFLUX_TOKEN> with valid ones.
Now the output is the same json but without the ‘%’ and ‘°C’. Because I needed to get a numerical value and set the required prefixes in graph.
I have used InfluxDB Data Point to write data.
Exported JSON of this minimal dashboard is-
{
"meta": {
"version": "1",
"type": "dashboard",
"name": "Temperature & Humidity via DHT22 Sensor-Template",
"description": "template created from dashboard: Temperature & Humidity via DHT22 Sensor"
},
"content": {
"data": {
"type": "dashboard",
"attributes": {
"name": "Temperature & Humidity via DHT22 Sensor",
"description": ""
},
"relationships": {
"label": {
"data": []
},
"cell": {
"data": [
{
"type": "cell",
"id": "08fc4b18c8fe1000"
},
{
"type": "cell",
"id": "08fc4b9c79fe1000"
},
{
"type": "cell",
"id": "08fc4dc3b5fe1000"
},
{
"type": "cell",
"id": "08fc4e064fbe1000"
}
]
},
"variable": {
"data": []
}
}
},
"included": [
{
"id": "08fc4b18c8fe1000",
"type": "cell",
"attributes": {
"x": 0,
"y": 0,
"w": 6,
"h": 3
},
"relationships": {
"view": {
"data": {
"type": "view",
"id": "08fc4b18c8fe1000"
}
}
}
},
{
"id": "08fc4b9c79fe1000",
"type": "cell",
"attributes": {
"x": 6,
"y": 0,
"w": 6,
"h": 3
},
"relationships": {
"view": {
"data": {
"type": "view",
"id": "08fc4b9c79fe1000"
}
}
}
},
{
"id": "08fc4dc3b5fe1000",
"type": "cell",
"attributes": {
"x": 6,
"y": 3,
"w": 6,
"h": 3
},
"relationships": {
"view": {
"data": {
"type": "view",
"id": "08fc4dc3b5fe1000"
}
}
}
},
{
"id": "08fc4e064fbe1000",
"type": "cell",
"attributes": {
"x": 0,
"y": 3,
"w": 6,
"h": 3
},
"relationships": {
"view": {
"data": {
"type": "view",
"id": "08fc4e064fbe1000"
}
}
}
},
{
"type": "view",
"id": "08fc4b18c8fe1000",
"attributes": {
"name": "Humidity",
"properties": {
"shape": "chronograf-v2",
"type": "gauge",
"queries": [
{
"text": "from(bucket: \"dht\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"_measurement\"] == \"humidity\")\n |> filter(fn: (r) => r[\"_field\"] == \"humidity\")\n |> filter(fn: (r) => r[\"host\"] == \"pi\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")",
"editMode": "advanced",
"name": "",
"builderConfig": {
"buckets": [],
"tags": [
{
"key": "_measurement",
"values": [],
"aggregateFunctionType": "filter"
}
],
"functions": [
{
"name": "mean"
}
],
"aggregateWindow": {
"period": "auto",
"fillValues": false
}
}
}
],
"prefix": "",
"tickPrefix": "",
"suffix": "%",
"tickSuffix": "%",
"colors": [
{
"id": "0",
"type": "min",
"hex": "#00C9FF",
"name": "laser",
"value": 0
},
{
"id": "1",
"type": "max",
"hex": "#9394FF",
"name": "comet",
"value": 100
}
],
"decimalPlaces": {
"isEnforced": true,
"digits": 2
},
"note": "",
"showNoteWhenEmpty": false
}
}
},
{
"type": "view",
"id": "08fc4b9c79fe1000",
"attributes": {
"name": "Temperature",
"properties": {
"shape": "chronograf-v2",
"type": "gauge",
"queries": [
{
"text": "from(bucket: \"dht\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"_measurement\"] == \"temperature\")\n |> filter(fn: (r) => r[\"_field\"] == \"temperature\")\n |> filter(fn: (r) => r[\"host\"] == \"pi\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")",
"editMode": "advanced",
"name": "",
"builderConfig": {
"buckets": [],
"tags": [
{
"key": "_measurement",
"values": [],
"aggregateFunctionType": "filter"
}
],
"functions": [
{
"name": "mean"
}
],
"aggregateWindow": {
"period": "auto",
"fillValues": false
}
}
}
],
"prefix": "",
"tickPrefix": "",
"suffix": "°C",
"tickSuffix": "°C",
"colors": [
{
"id": "0",
"type": "min",
"hex": "#FFD255",
"name": "thunder",
"value": 0
},
{
"id": "1",
"type": "max",
"hex": "#F95F53",
"name": "curacao",
"value": 100
}
],
"decimalPlaces": {
"isEnforced": true,
"digits": 2
},
"note": "",
"showNoteWhenEmpty": false
}
}
},
{
"type": "view",
"id": "08fc4dc3b5fe1000",
"attributes": {
"name": "Temperature Graph",
"properties": {
"shape": "chronograf-v2",
"queries": [
{
"text": "from(bucket: \"dht\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"_measurement\"] == \"temperature\")\n |> filter(fn: (r) => r[\"_field\"] == \"temperature\")\n |> filter(fn: (r) => r[\"host\"] == \"pi\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")",
"editMode": "advanced",
"name": "",
"builderConfig": {
"buckets": [],
"tags": [
{
"key": "_measurement",
"values": [],
"aggregateFunctionType": "filter"
}
],
"functions": [
{
"name": "mean"
}
],
"aggregateWindow": {
"period": "auto",
"fillValues": false
}
}
}
],
"axes": {
"x": {
"bounds": [
"",
""
],
"label": "",
"prefix": "",
"suffix": "",
"base": "10",
"scale": "linear"
},
"y": {
"bounds": [
"",
""
],
"label": "Temperature",
"prefix": "",
"suffix": "°C",
"base": "10",
"scale": "linear"
}
},
"type": "xy",
"staticLegend": {
"colorizeRows": true,
"opacity": 1,
"orientationThreshold": 100000000,
"widthRatio": 1
},
"geom": "line",
"colors": [
{
"id": "ec36837f-84bd-43b6-be10-970343f0bbca",
"type": "scale",
"hex": "#8F8AF4",
"name": "Do Androids Dream of Electric Sheep?",
"value": 0
},
{
"id": "ad64f52f-fadd-48ca-9365-98e8a5e3ce39",
"type": "scale",
"hex": "#A51414",
"name": "Do Androids Dream of Electric Sheep?",
"value": 0
},
{
"id": "6a1fc916-9b65-481f-b0df-7662b75468d8",
"type": "scale",
"hex": "#F4CF31",
"name": "Do Androids Dream of Electric Sheep?",
"value": 0
}
],
"note": "",
"showNoteWhenEmpty": false,
"xColumn": "_time",
"generateXAxisTicks": [],
"xTotalTicks": 0,
"xTickStart": 0,
"xTickStep": 0,
"yColumn": "_value",
"generateYAxisTicks": [],
"yTotalTicks": 0,
"yTickStart": 0,
"yTickStep": 0,
"shadeBelow": false,
"position": "overlaid",
"timeFormat": "",
"hoverDimension": "auto",
"legendColorizeRows": true,
"legendHide": false,
"legendOpacity": 1,
"legendOrientationThreshold": 100000000
}
}
},
{
"type": "view",
"id": "08fc4e064fbe1000",
"attributes": {
"name": "Humidity Graph",
"properties": {
"shape": "chronograf-v2",
"queries": [
{
"text": "from(bucket: \"dht\")\n |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n |> filter(fn: (r) => r[\"_measurement\"] == \"humidity\")\n |> filter(fn: (r) => r[\"_field\"] == \"humidity\")\n |> filter(fn: (r) => r[\"host\"] == \"pi\")\n |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)\n |> yield(name: \"mean\")",
"editMode": "advanced",
"name": "",
"builderConfig": {
"buckets": [],
"tags": [
{
"key": "_measurement",
"values": [],
"aggregateFunctionType": "filter"
}
],
"functions": [
{
"name": "mean"
}
],
"aggregateWindow": {
"period": "auto",
"fillValues": false
}
}
}
],
"axes": {
"x": {
"bounds": [
"",
""
],
"label": "",
"prefix": "",
"suffix": "",
"base": "10",
"scale": "linear"
},
"y": {
"bounds": [
"",
""
],
"label": "Humidity",
"prefix": "",
"suffix": "%",
"base": "10",
"scale": "linear"
}
},
"type": "xy",
"staticLegend": {
"colorizeRows": true,
"opacity": 1,
"orientationThreshold": 100000000,
"widthRatio": 1
},
"geom": "line",
"colors": [
{
"id": "c98cc8b9-7e68-4355-8087-2e26c682386d",
"type": "scale",
"hex": "#DA6FF1",
"name": "Ectoplasm",
"value": 0
},
{
"id": "c817625b-9b18-4202-806f-bcec388a7333",
"type": "scale",
"hex": "#00717A",
"name": "Ectoplasm",
"value": 0
},
{
"id": "0806b63a-2228-49d8-8a31-dfd8cbcf9912",
"type": "scale",
"hex": "#ACFF76",
"name": "Ectoplasm",
"value": 0
}
],
"note": "",
"showNoteWhenEmpty": false,
"xColumn": "_time",
"generateXAxisTicks": [],
"xTotalTicks": 0,
"xTickStart": 0,
"xTickStep": 0,
"yColumn": "_value",
"generateYAxisTicks": [],
"yTotalTicks": 0,
"yTickStart": 0,
"yTickStep": 0,
"shadeBelow": false,
"position": "overlaid",
"timeFormat": "",
"hoverDimension": "auto",
"legendColorizeRows": true,
"legendHide": false,
"legendOpacity": 1,
"legendOrientationThreshold": 100000000
}
}
}
]
},
"labels": []
}
I have other plans to use the DHT-22 like controlling exhaust fan or similar. Maybe later. For now, I will just collect data and observe the fluctuation of my rooms temperature and humidity.
It was fun working with InfluxDB and DHT-22 with RaspberryPI.
Thanks for reading. Please give me feedback If you have idea for me or point me some improvements.