Data Upload API & Samples scripts

The first step is to get a token from data-platform page.

Once you have your own token, you can use the following script to upload your data. After you upload your first station data, go to aqicn.org/data-feed/verification/ to configure your stations and verify the uploaded data.

Supported Software Platforms:

We provide the ready to use software for those 3 platforms:

  • Arduino: If you have an Arduino CPU, use the ready-to-use software available on github.com at aqicn/gaia-a08-arduino.
  • Python: Use the code-snippet below
  • Command line (CURL): Use the code-snippet below

If you do not have any monitoring station, and would like to get one, check our GAIA Air Quality monitoring stations.

If you prefer a DIY station, check the GAIA A08.


--

Sample code (python)

import requests  
 
# Sensor parameter   
sensorReadings = [   
	{'specie':'pm25', 'value': 393.3},  
	{'specie':'pm10', 'value': 109.3}  
] 
 
# Station parameter   
station = { 
	'id':		"station-001",  
	'location':  { 
		'latitude': 28.7501,  
		'longitude': 77.1177 
	} 
} 
 
# User parameter - get yours from https://aqicn.org/data-platform/token/ 
userToken = "dummy-token-for-test-purpose-only" 
 
# Then Upload the data  
params = {'station':station,'readings':sensorReadings,'token':userToken}  
request = requests.post( url = "https://aqicn.org/sensor/upload/",  json = params) 
#print(request.text) 
data = request.json()  
 
if data["status"]!="ok": 
	print("Something went wrong: %s" % data) 
else: 
	print("Data successfully posted: %s"%data) 

Sample code (curl)

curl -X POST https://aqicn.org/sensor/upload -H 'Content-Type: application/json' --data '{\ 
"token": "dummy-token-for-test-purpose-only",\ 
"station": { "id": "station-001" },\ 
"readings": [{"specie":"pm2.5", "value": 393.3}]\ 
}'

Sample code (arduino)

Check github.com/aqicn/gaia-a08-arduino for the full code.
#include <WiFi.h> 
#include <HTTPClient.h> 
#include <ArduinoJson.h> 
 
#define LATITUDE 28.7501 
#define LONGITUDE 77.1177 
 
void upload(float pm25_concentration, float pm10_concentration, const char * token) 
{ 
 
    static char stationID[32]; 
    uint64_t efuseMac = ESP.getEfuseMac(); 
    uint16_t chip = (uint16_t)(efuseMac >> 32); 
    snprintf(stationID, 32, "station-%x", chip); 
 
    doc["token"] = token; 
    doc["station"]["id"] = stationID; 
 
    doc["station"]["location"]["latitude"] = LATITUDE; 
    doc["station"]["location"]["longitude"] = LONGITUDE; 
 
    doc["readings"][0]["specie"] = "pm25"; 
    doc["readings"][0]["value"] = pm25_concentration; 
    doc["readings"][0]["unit"] = "µg/m3"; 
 
    doc["readings"][1]["specie"] = "pm10"; 
    doc["readings"][1]["value"] = pm10_concentration; 
    doc["readings"][1]["unit"] = "µg/m3"; 
 
    static char json_body[1024]; 
    serializeJson(doc, json_body); 
 
    HTTPClient http; 
    http.begin("https://aqicn.org/sensor/upload"); 
    http.addHeader("Content-Type", "application/json"); 
    int httpResponseCode = http.POST(json_body); 
 
    if (httpResponseCode > 0) 
    { 
 
        String response = http.getString(); 
        Serial.println(httpResponseCode); 
        Serial.println(response); 
    } 
    else 
    { 
 
        Serial.print("Error on sending POST: "); 
        Serial.println(httpResponseCode); 
    } 
 
    http.end(); 
}

API Options

Parameter Type Optional/Mandatory Explanations
token string mandatory

Get your own token from aqicn.org/data-platform/token.

station
station.id string mandatory

Unique station ID - you can select any name with max 128 characters.
This name is only used internally for you. No one else will see this ID

station.name string optional

Name of the station - could be for instance the name of your building, the name of a street, the name of a university departement, the code of your personal weather station.
This name will be used as the suffix for your station URL.

station.latitude float optional

Longitude of your station

station.longitude float optional

Longitude of your station

organization
org.website string optional

If you have a website with more information about your station/sensor, we will add this link on our map when used see your station

org.name string optional

If you specify a website, this "organization name" will be associated to the website.

readings
readings[*].specie string mandatory

Name of the pollutant your are reporting. For gas sensors, use: "pm2.5", "pm10", "pm1.0", ... For gaz sensor, use: "co2", "no2", "o3", ... For weather sensor, use: "temp", "humidity", "pressure", "wind speed", "wind gust", "wind direction", ..
You can actually use any specie name you want. When you station is validated, the names will be normalized in our system.

readings[*].value float mandatory

If your sensor is producing values every second, and you only upload every minute, this value should be the average of all the values read during the past minute.

readings[*].unit string optional

Unit of the value. Eg "mg/m3" for dust sensor, ppb for gas sensors, C for temp sensor..

readings[*].time string optional

Date and Time of the reading in ISO 8601 format

readings[*].min float optional

If the reading values are based on the averaging of several values, then this correspond to the min value of all values used for the averaging.

readings[*].max float optional

If the reading values are based on the averaging of several values, then this correspond to the max value of all values used for the averaging.

readings[*].median float optional

If the reading values are based on the averaging of several values, then this correspond to the median value of all values used for the averaging.

readings[*].stddev float optional

If the reading values are based on the averaging of several values, then this correspond to the standard deviation of all values used for the averaging.

readings[*].averaging float optional

If the above values are based on the averaging of several values, then this correspond to the duration, in seconds, of the averaging period.
For instance, use 60 for a minute average data and 3600 for hourly average.

Example 1

{ 
	"token": "......", 
	"station": { 
		"id": "station-001", 
		"name": "HCPA Santa Cecília", 
		"latitude": 103.37893, 
		"longitude": 43.17108, 
	}, 
	"org": { 
		"website":"https://pacto.upsensor.com/", 
		"name":"Porto Ar Alegre", 
	}, 
	"readings": [ 
		{"time":"2024-04-24T22:06:01+09:00","specie":"pm2.5", "value": 393.3, "unit":"mg/m3", "min":390.3, "max": 402.3, "stddev": 0.332},  
		{"time":"2024-04-24T22:06:01+09:00","specie":"pm10", "value": 109.3, "unit":"mg/m3"}, 
		{"time":"2024-04-24T22:06:01+09:00","specie":"co2", "value": 459.3, "unit":"ppb"}, 
		{"time":"2024-04-24T22:06:01+09:00","specie":"temp", "value": 26.8, "unit":"C"}, 
	] 
}

Example 2

{ 
	"token": "......", 
	"station": { 
		"id": "station-001", 
	}, 
	"readings": [ 
		{"specie":"pm2.5", "value": 393.3} 
	] 
}

Complete Code example

You can use this code for continuously reading from an SDS sensor, and uploading every minute: (script also available from https://github.com/aqicn/sds-sensor-reader).

import requests 
import random 
import time 
import math 
import json 
import sys 
from serial import Serial 
 
LOCATION = {'latitude': 28.7501, 'longitude': 77.1177} 
TOKEN    = "dummy-token-for-test-purpose-only" 
SENSORID = "station-001" 
USBPORT  = "/dev/ttyUSB0" 
 
class SensorDataUploader: 
 
    def __init__(self, station, token): 
        self.token = token 
        self.station = station 
 
 
    def send(self,readings): 
 
        params = {'station':self.station,'readings':readings,'token':self.token}  
        print("Uploading: %s"%json.dumps(params, indent=4)) 
 
        request = requests.post( url = "https://aqicn.org/sensor/upload/",  json = params) 
        data = request.json()  
        if data["status"]!="ok": 
            print("Something went wrong: %s" % data) 
        else: 
            print("Data successfully posted: %s"%data) 
 
 
 
 
class Accumulator: 
 
    def __init__(self, name): 
        self.name = name 
        self.values = [] 
 
    def add(self,val): 
        self.values.append(val) 
 
    def count(self): 
        return len(self.values) 
 
    def reset(self): 
        self.values=[] 
 
    def min(self): 
        return self.values[0] 
 
    def max(self): 
        return self.values[len(self.values)-1] 
 
    def median(self): 
        return self.values[len(self.values)/2] 
 
    def mean(self): 
        return float(sum(self.values)) / len(self.values) 
 
    def stddev(self): 
        l = len(self.values) 
        mean = self.mean() 
        return math.sqrt(float(reduce(lambda x, y: x + y, map(lambda x: (x - mean) ** 2, self.values))) / l) 
 
 
    def summary(self): 
        self.values.sort() 
        return {"specie":self.name,'value':self.mean(),'min':self.min(),'max':self.max(),'median':self.median(), 'stddev':self.stddev()}  
 
 
 
class DummyReader: 
 
    def read( self ): 
 
        time.sleep(1.1) 
        return {"pm2.5":random.random()*10,"pm10":random.random()*10} 
 
 
class SDS011Reader: 
 
    def __init__(self, inport): 
        self.serial = Serial(port=inport,baudrate=9600) 
        self.values = [] 
        self.step = 0 
 
    def read( self ): 
 
        # time.sleep(1) 
        # return {"pm2.5":random.random()*100,"pm10":random.random()*100} 
 
        while self.serial.inWaiting()!=0: 
            v=ord(self.serial.read()) 
 
            if self.step ==0: 
                if v==170: 
                    self.step=1 
 
            elif self.step==1: 
                if v==192: 
                    self.values = [0,0,0,0,0,0,0] 
                    self.step=2 
                else: 
                    self.step=0 
 
            elif self.step>8: 
                self.step =0 
                pm25 = (self.values[0]+self.values[1]*256)/10 
                pm10 = (self.values[2]+self.values[3]*256)/10 
                return {"pm2.5":pm25,"pm10":pm10} 
 
            elif self.step>=2: 
                self.values[self.step-2]=v 
                self.step= self.step+1 
 
        return None 
 
 
 
def readAndUpload(sensor, uploader): 
 
    try: 
 
        while True: 
            accumulators = {} 
            startTime = time.time() 
 
            while time.time() < startTime+60: 
                values = sensor.read() 
                if values==None: 
                    continue 
 
                print("Reading [%2d]: %s"%(int(time.time()-startTime),values)) 
                for specie, value in values.items(): 
                    if not (specie in accumulators): 
                        accumulators[specie]=Accumulator(specie) 
                    accumulators[specie].add(value) 
 
 
            readings = [] 
            for specie, accumulator in accumulators.items(): 
                readings.append(accumulator.summary()) 
 
            if len(readings)>0: 
                uploader.send(readings) 
            else: 
                print("No value read from the sensor...") 
 
 
    except KeyboardInterrupt: 
        print "Bye" 
        sys.exit() 
 
 
 
print("Starting reading sensor "+SENSORID+" on port "+USBPORT) 
 
# Station parameter   
station = {'id':SENSORID, 'location':LOCATION} 
uploader = SensorDataUploader(station, TOKEN) 
 
sensor = SDS011Reader(USBPORT) 
# sensor = DummyReader() 
readAndUpload(sensor,uploader) 
 

Measure the air quality in your neighborhood
Participate with your own air quality monitoring station

The GAIA air quality monitor uses laser particle sensors to measure in real-time PM2.5 and PM10 particle pollution, which is one of the most harmful air pollutants.

It is very easy to set up: It only requires a WIFI access point and a USB compatible power supply. Once connected, your real time air pollution levels are instantaneously available in on our maps.

The station comes together with 10-meter water-proof power cables, a power supply, mounting equipment and an optional solar panel.

About the Air Quality and Pollution Measurement:

About the Air Quality Levels

AQI Air Pollution Level Health Implications Cautionary Statement (for PM2.5)
0 - 50 Good Air quality is considered satisfactory, and air pollution poses little or no risk None
51 -100 Moderate Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution. Active children and adults, and people with respiratory disease, such as asthma, should limit prolonged outdoor exertion.
101-150 Unhealthy for Sensitive Groups Members of sensitive groups may experience health effects. The general public is not likely to be affected. Active children and adults, and people with respiratory disease, such as asthma, should limit prolonged outdoor exertion.
151-200 Unhealthy Everyone may begin to experience health effects; members of sensitive groups may experience more serious health effects Active children and adults, and people with respiratory disease, such as asthma, should avoid prolonged outdoor exertion; everyone else, especially children, should limit prolonged outdoor exertion
201-300 Very Unhealthy Health warnings of emergency conditions. The entire population is more likely to be affected. Active children and adults, and people with respiratory disease, such as asthma, should avoid all outdoor exertion; everyone else, especially children, should limit outdoor exertion.
300+ Hazardous Health alert: everyone may experience more serious health effects Everyone should avoid all outdoor exertion

To know more about Air Quality and Pollution, check the wikipedia Air Quality topic or the airnow guide to Air Quality and Your Health.

For very useful health advices of Beijing Doctor Richard Saint Cyr MD, check www.myhealthbeijing.com blog.


Usage Notice: All the Air Quality data are unvalidated at the time of publication, and due to quality assurance these data may be amended, without notice, at any time. The World Air Quality Index project has exercised all reasonable skill and care in compiling the contents of this information and under no circumstances will the World Air Quality Index project team or its agents be liable in contract, tort or otherwise for any loss, injury or damage arising directly or indirectly from the supply of this data.



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