Categories
circuits Internet of Things microcontrollers sensors Software weather station

Weather Station Wind Vane

What types of sensor can be used for a weather vane? How to track angular position using a rotary encoder? How easy is calibration? What coding considerations for a weather station wind direction project?

Mesopotamian base-60 number system resulted in our idea of 360° in a full circle. Early compasses described 32 points and eight cardinal directions of wind, serving as navigational aids for maritime exploration.

References recorded in ancient China as early as 139 BC described “wind observing fan”. In classical Greece astronomer Andronicus constructed a weather vane at “tower of winds” in Athens. Weather vanes were known in many places of antiquity.

The word “vane” derives from Old English “fane” (Germanic Fahne) signifying “cloth, banner, flag” all of which can be deployed as visual wind direction indicators.

In modern times, absolute and incremental encoders are sensor devices measuring rotary position (angle) and motion. Resolution, precision and accuracy have distinct meaning.

Absolute encoders maintain position during power off or device reset. Incremental motion encoder data is relative, sensors of this type require “homing” (passing a known position) to calibrate.

Lets consider some types of rotary encoder

  • magnetic rotary encoder
  • 360° Potentiometer
  • optical encoder
  • magnetic sensor array

Magnetic Rotary Encoder

Contactless magnetic encoders track a dipole magnet attached to a rotating shaft above sensor, recording rotational angle and direction through a full turn of 360° with high resolution and precision.

Internally hall sensors measure angular position of a magnetic field presented at surface, converting this to a voltage.

On chip digital signal processing (DSP) amplifies and filters planar field data before conversion by Analogue to Digital conversion (ADC).

Having no mechanical friction leads to long expected life span.

A wide operating temperature range (-40 Deg.C to 150 Deg.C) and environmental tolerances (~80% humidity) allow for a wide potential application range.

2/3 wire I2C/SPI programmable interfaces provide standardised micro-controller connectivity and control.

AS5600 Datasheet
MLX90316 Datasheet

Potentiometer 360 degree

Several commercial wind vanes targeted at maritime applications deploy a 360° potentiometer connected directly to vane shaft.

Having a compact, space efficient design, high resolution (degrees of direction) can be tracked.

Detent (stops or clicks) add rotational resistance and a fixed set of positions but increase friction.

Electro-mechanical contacts are subject to mechanical wear and surface corrosion of contact track impacting accuracy, durability and longevity.

Optical Encoder

Optical incremental encoders – IR LED / Sensor pair with a spinning disk interrupter are accurate at very high RPM rates with low sensor latency (rise time).

Resolution is determined by interrupt light “chopper” disk design and relative position is measured by counting rotational sensor ticks.

Quadrature or two channel encoding, with a phase offset, is employed to determine rotational direction.

Calibration, including between device reset/power off is a challenge – sensor pulse counting during rotation must be relative to a fixed/known initial position.

Magnetic Sensor Array

Early compasses recorded 32 points to indicate winds as a navigational aid to sailors.

Wiring 32 sensors together requires considerable soldering & assembly skill. If 4 or 8 bit resolution is sufficient, magnetic linear hall or reed switches might be used – both are contactless, low cost and widely available.

Sensors arranged in a ring array activated by a rotating magnet allow a micro-controller to track position changes.

One approach is to use polling and a GPIO pin per sensor. Pin change interrupts can also be used for state notification.

An analogue multiplexer (CD4051) reduces number of required input pins to 4 (3 address pins, 1 data), optionally a common interrupt enables this to work with an event (interrupt) driven model.

Sensor Implementation – Polling vs Event Model

Polling, reading position at a set frequency (interval), provides consistency and allows simple computation analysis – roll-up averages for example. Higher frequency sampling results in higher precision.

In event model – an interrupt is triggered when sensor state (position) changes.

Recording position data only when direction changes is a low power consumption approach, extending operating duration of a battery powered device, especially on windless days.

To implement event driven design with a multiplexer poses a challenge, at circuit level a common interrupt line wired with isolating diodes to each sensor is required.

A change to any individual sensor triggers an interrupt, micro-controller can then check each multiplexer channel to determine position.

Calibration – how to determine magnetic north?

A compass bearing is required to determine direction relative to cardinal directions.

Wind vanes in a fixed position are manually calibrated. Electronic sensor devices can resolve orientation relative to magnetic compass.

Wind direction is defined by World Geodetic System (WGS) as direction from which wind blows and is measured clockwise from geographical north, namely, true north (meteorology) or in aviation reporting relative to magentic north. 

Visualisation – Wind Rose and Polar Distribution Charts

Wind roses, a type of polar bar chart provide a visualisation of wind distribution: direction and magnitude (velocity) frequency at a location over a given time interval.

Categories
arduino circuits Coding Internet of Things microcontrollers sensors Software

Weather Vane – Magnetic Sensor Rotary Encoder

A ring of 8 magnetic digital hall sensors (one per cardinal direction) are activated by a rotating neodymium magnet attached to a shaft, creating a simple rotary encoder.

Hall Effect Magnetic Sensor array connected to Arduino UNO microcontroller.

Input Pull-Up Resistors

Each hall effect sensor is wired to a digital micro-controller pin.

To prevent “floating”, input pin state is biased HIGH using pull-up resistors .

External pull-up 10k resistors are connected between hall effect sensor 5v+ and digital out pins.

If no external resistors are present GPIO pins should be setup as INPUT_PULLUP activating microcontroller internal 20k pull up resistor.

Polling for Active Pin

Each iteration of loop() reads input pins to determine active sensor.

// current and previous active sensor pin
int active = NULL;
int lastActive = NULL;

void loop() {

  int v;
  active = 0;

  for(int i = 3; i <= 10; i++)
  {
    v = digitalRead(i);

    if (v == 0)
    {
      active = i;
    }
  }
  if (active == 0) // magnet between sensor positions
  {
      active = lastActive;      
  }
  if (active != lastActive)
  {
    Serial.print(active);
    Serial.print("\t");
    Serial.println(directionLabel[active-3]);
  }

  lastActive = active;
}

Variables are maintained to track current and previous activation, direction is updated on position change.

If magnet is between sensor positions and no pin is active, last active position is reported.

Compass Direction Labels

Finally pin number is translated to direction (“N”, “NE”, “E” etc) by indexing into an ordered character pointer array.

// pin order direction labels
char d0[] = "NE";
char d1[] = "SE";
char d2[] = "E";
char d3[] = "S";
char d4[] = "N";
char d5[] = "W";
char d6[] = "NW";
char d7[] = "SW";

char * directionLabel[] = { d0, d1, d2, d3, d4, d5, d6, d7 };

...
// i == active sensor pin number 3 - 10 
Serial.println(directionLabel[i-3]);

Interrupts – Event Driven

Instead of polling (reading sensors on each loop() iteration) we can minimise processing and power consumption by updating direction only when magnet position changes.

Less power is consumed reading current position from a variable in flash memory compared to reading each sensor input pin – decoupling logic to maintain position from code reporting current value increases efficiency.

On Arduino (Uno, Nano etc) by default specific pins trigger external interrupts. Any GPIO pin can be used as an interrupt trigger with pin change interrupts.

To setup pin-change interrupts for digital pins 3 – 10 :

volatile int irqState = 0;
unsigned long lastIrq;
int irqDelay = 100; // millisecs

ISR (PCINT0_vect) 
{
  irqState = 1; 
}

ISR(PCINT2_vect)
{
  irqState = 1; 
}

void setupPinChangeInterrupt()
{
  cli();

  // 1 – Turn on Pin Change Interrupts
  PCICR |= 0b00000001;      // turn on port b (PCINT0 – PCINT7) pins D8 - D13
  PCICR |= 0b00000100;      // turn on port d (PCINT16 – PCINT23) pins D0 - D7

  // 2 – Choose Which Pins to Interrupt ( 3 mask registers correspond to 3 INT ports )
  PCMSK0 |= 0b00000111;    // turn on pins D8,D9,D10
  PCMSK2 |= 0b11111000;    // turn on pins D3 - D7 (PCINT19 - 23)

  sei();                     // turn on interrupts
}

A full example of setting up Arduino pin change interrupts, checking state and reading pins from data register can be found on github and there’s a useful guide here.

Now in loop() we can check for active pin only when interrupt event occurs, software de-bounce timeout prevents multiple repeat activations:

void loop() {

  if (irqState == 1 &amp;&amp; (millis() - lastIrq > irqDelay))
  {

    // check for active pin...

    lastIrq = millis();
    irqState = 0;
  }
}

Hardware Common Interrupt

A more portable solution can be implemented in hardware by adding a common interrupt line from each Hall Sensor input, isolating switch input with a diode which conducts only in one direction.

Now a change to any sensor input causes common interrupt (pin D2) to go LOW, signalling to micro-controller to check and update active magnet position.

1N4148 High Speed Signal Diode isolate common interrupt line

A single external interrupt can be handled by Arduino Uno/Nano pin D2

attachInterrupt(0, pin2IRQ, FALLING);

Power consumption can be reduced further by implementing deep sleep between sensor change interrupts, waking only to update state or transmit position data at intervals.

Arduino Nano v3 micro-controller tracking interrupt triggered magnetic switch position

Real Time Wind Compass Web Interface

D3.js Wind Compass UI has a design inspired by Dieter Rams who worked for Braun and is single HTML file adapted from a simple clock.

Units range is changed to 360 divided into sub-divisions of 10 and 45 (8 compass directions).

User Interface (UI) Data Provisioning

A finished product might transmit data wirelessly using LORA, Wifi, Bluetooth or 433mhz RF.

For prototype testing we can use serialToWebsocket.py a script based on Python’s PySerial library to capture serial console output and relay this to a websocket.

python3 serialToWebsocket.py 
connected to: /dev/ttyUSB0

3	S
5	SW
4	W
6	NW

We can use Python to run a simple webserver to develop and test our interface –

python -m SimpleHTTPServer 3001

Wind Compass can now be loaded in a browser –

http://127.0.0.1:3001/wsWindCompass.html

UI demo and source code can be found below –

See it in action –

Full source code can on github:

Arduino Wind Vane Sketch:
https://github.com/steveio/arduino/tree/master/WindVane8HallSensor
Wind Compass D3.js Web UI:
https://github.com/steveio/mqttWebSocket/blob/master/wsWindCompass.html
Serial to Websocket Python Script
https://github.com/steveio/arduino/blob/master/python/serialToWebsocket.py

Categories
arduino Coding Internet of Things nodejs Python Software

MQTT to Websockets with ESP32, NodeJS and D3.js

MQTT is a lightweight messaging protocol suitable for embedded and IOT devices.

Websockets ( RFC6455 – https://tools.ietf.org/html/rfc6455 ) is socket programming for internet, an evolution of browser / web server HTTP enabling real-time bidirectional data exchange and binary messaging.

How do we interface a MQTT enabled IOT sensor device with a web browser interface displaying a real time graph chart?

A real time web based barometric air pressure chart interface created with WebSockets and D3.js

Introduction to WebSockets – Real Time TCP Sockets for Internet

With modern browser engines and responsive web UI technologies built on HTML5, SVG and JavaScript frameworks, sophisticated visualisation, display and dashboard reporting capabilities have emerged.

Responsive Web UI runs in any browser installed device – laptop, dekstop, tablet or mobile, without need to install additional software or prepare application code for specific device architectures.

HTTP browser clients essentially implement a polling request/response technique for retrieving and updating HTML format webpages.

Due to need to establish a connection for each new request, HTTP is not well suited to real time or high volume messaging, charting or visualisation applications.

Although AJAX (asynchronous JavaScipt XML) and REST, SOAP API programming overcome this to a certain extent these methods are relatively inefficient for some use cases due to protocol overhead.

With Websockets, TCP network socket programming becomes possible in a browser client application.

Clients can establish a network socket connection, this channel remains open and two-way data exchange including binary messaging formats takes place.

Sockets are well established in UNIX and Windows OS client/server programming, but are relatively new to the web.

Arduino ESP32 Barometer Sensor MQTT Device

An ESP32 microcontroller with BMP280 environmental sensor and OLED LCD display

An environmental sensor based on an Expressif ESP32 micro-controller and BMP280 Bosch sensor reads air pressure, temperature and altitude –

#include <Adafruit_BMP280.h>

Adafruit_BMP280 bmp;

void setup() {

  if (!bmp.begin()) {
    Serial.println(F("Could not find a valid BMP280 sensor, check wiring!"));
    while (1);
  }
  
  /* Default settings from datasheet. */
  bmp.setSampling(Adafruit_BMP280::MODE_NORMAL,     /* Operating Mode. */
                  Adafruit_BMP280::SAMPLING_X2,     /* Temp. oversampling */
                  Adafruit_BMP280::SAMPLING_X16,    /* Pressure oversampling */
                  Adafruit_BMP280::FILTER_X16,      /* Filtering. */
                  Adafruit_BMP280::STANDBY_MS_500); /* Standby time. */  

}

void loop() {

  Serial.print(F("Temperature = "));
  Serial.print(bmp.readTemperature());
  Serial.println(" *C");

  Serial.print(F("Pressure = "));
  Serial.print(bmp.readPressure()/100); //displaying the Pressure in hPa, you can change the unit
  Serial.println(" hPa");

  Serial.print(F("Approx altitude = "));
  Serial.print(bmp.readAltitude(1019.66)); //The "1019.66" is the pressure(hPa) at sea level in day in your region
  Serial.println(" m");                    //If you don't know it, modify it until you get your current altitude

  display.clearDisplay();
  float t = bmp.readTemperature();           //Read temperature in C
  float p = bmp.readPressure()/100;         //Read Pressure in Pa and conversion to hPa
  float a = bmp.readAltitude(1019.66);      //Calculating the Altitude, the "1019.66" is the pressure in (hPa) at sea level at day in your region

  delay(2000);
}

Data is communicated over Wifi to an MQTT messaging server.

On Arduino we can use PubSub MQTT Library ( https://github.com/knolleary/pubsubclient ).

To set this up, first we define Wifi and MQTT server credentials and topic id (channels) and define a transmit data buffer:

const char* ssid = "__SSID__";
const char* pass = "__PASS__";

IPAddress mqtt_server(192, 168, 1, 127); // local LAN Address
const char* mqtt_user = "mqtt";
const char* mqtt_password = "__mqttpassword__";

const char* mqtt_channel_pub = "esp32.out";
const char* mqtt_channel_sub = "esp32.in";

WiFiClient wifi;
PubSubClient mqtt(wifi);

#define MSG_BUFFER_SIZE (128)
char msg[MSG_BUFFER_SIZE];

Then we setup Wifi connection:

  WiFi.begin(ssid, password);

  while (WiFi.status() != WL_CONNECTED) {
    delay(500);
    Serial.print(".");
  }

  Serial.println("");
  Serial.println("WiFi connected");
  Serial.print("Connecting to ");
  Serial.println(ssid);
  Serial.println("IP address: ");
  Serial.println(WiFi.localIP());

And attempt to connect to MQTT broker, sending a hello message:

void loop() {
  
  while (!mqtt.connected()) {
    Serial.print("Attempting MQTT connection...");
    // Create a random client ID
    String clientId = "ESP8266Client-";
    clientId += String(random(0xffff), HEX);
    // Attempt to connect
    if (mqtt.connect(clientId.c_str(), mqtt_user, mqtt_password)) {
      Serial.println("connected");
      // Once connected, publish an announcement...
      mqtt.publish(mqtt_channel_pub, "hello ESP32");
      // ... and resubscribe
      mqtt.subscribe(mqtt_channel_sub);
    } else {
      Serial.print("failed, rc=");
      Serial.print(mqtt.state());
      Serial.println(" try again in 5 seconds");
      // Wait 5 seconds before retrying
      delay(5000);
    }
  }

  mqtt.loop();
}

After reading, we can transmit sensor values (Temperature T, Pressure P, Altitude A) on ESP32:

  snprintf(msg, MSG_BUFFER_SIZE, "%.2f,%.2f,%.2f", t, p, a);

  Serial.print("Publish message: ");
  Serial.println(msg);
  mqtt.publish(mqtt_channel_pub, msg);

MQTT to WebSocket RFC6455 – Node.JS Relay

On server we require a relay to subscribe for MQTT messages on sensor device channel, establish a WebSocket and write data to connected browser clients.

An implementation in NodeJS requires WS, MQTT and events libraries:

// setup Websocket Server
const WebSocket = require('ws');
var ws_host = "192.168.1.127";
var ws_port = "8080";
const wss = new WebSocket.Server({ host: ws_host, port: ws_port });
var ws = null;

// Setup MQTT Client
// mqtt[s]://[username][:password]@host.domain[:port]
var mqtt = require('mqtt'), url = require('url');
var mqtt_url = url.parse(process.env.MQTT_URL || 'mqtt://192.168.1.127:1883');
var auth = (mqtt_url.auth || ':').split(':');
var url = "mqtt://" + mqtt_url.host;
var mqtt_channel_in = "esp8266.in";
var mqtt_channel_out = "esp8266.out";

var options = {
    port: mqtt_url.port,
    clientId: 'mqttjs_' + Math.random().toString(16).substr(2, 8),
    username: 'mqtt',
    password: '__mqtt_password__',
    keepalive: 60,
    reconnectPeriod: 1000,
    protocolId: 'MQIsdp',
    protocolVersion: 3,
    clean: true,
    encoding: 'utf8'
};

NodeJS is event based, when an MQTT message is received it can be forwarded to all connected WebSocket clients:

mqttClient.on('message', function sendMsg(topic, message, packet) {

  console.log(topic + ": " + message);

  var eventListeners = require('events').EventEmitter.listenerCount(mqttClient,'message');
  console.log(eventListeners + " Listner(s) listening to mqttClient message event");
  console.log(mqttClient.rawListeners('message'));

  wss.clients.forEach(function each(ws) {
    if (ws.isAlive === false) return ws.terminate();
    console.log(data);
    ws.send(data+" ");
  });

});

MQTT allows many subscribers to receive topic messages.

Python Eclipse Paho MQTT client with Mongo DB

A client based on Eclipse Paho ( https://www.eclipse.org/paho/ ) developed in Python might add persistence by writing to a Mongo DB datastore:

### Python MQTT client
### Subscribes to an MQTT topic receiving JSON format messages in format:
###    [{"ts":1586815920,"temp":22.3,"pressure":102583,"alt":76}]
###
### Writes receieved JSON data to a mongo DB collection
###
import paho.mqtt.client as mqtt
import json
import pymongo

mqtt_server = "192.168.1.127"
mqtt_port = 1883
mqtt_keepalive = 60
mqtt_channel_out = "esp8266.out"
mqtt_channel_in = "esp8266.in"

mongo_server = "mongodb://localhost:27017/"
mongo_db = "weather"
mongo_collection = "sensorData"

def on_connect(client,userdata,flags,rc):
    print("Connected with result code:"+str(rc))
    print ("MQTT server: "+mqtt_server+", port: "+str(mqtt_port));
    print ("MQTT topic: "+mqtt_channel_out);
    client.subscribe(mqtt_channel_out)

def on_message(client, userdata, msg):
    print(msg.payload)
    parsed_json = (json.loads(msg.payload))
    res = sensorData.insert_one(parsed_json[0])

mongoClient = pymongo.MongoClient(mongo_server)
mydb = mongoClient[mongo_db]
sensorData = mydb[mongo_collection]

mqttClient = mqtt.Client()
mqttClient.connect(mqtt_server,mqtt_port,mqtt_keepalive);

mqttClient.on_connect = on_connect
mqttClient.on_message = on_message

mqttClient.loop_forever()

Web Browser Client – D3.js WebSocket Real Time Chart

WebSockets are supported natively in JavaScript by modern browser clients.

Setting up a WebSocket client, we consider re-connect attempts and parse received message data (JSON format in this example):

      <script type="text/javascript">

        var dataArr = [];

        var ws = null
        var maxReconnectAttemps = 10;
        var reconnectAttempts = 0;

        // setup WebSocket
        function setupWebSocket()
        {

          reconnectAttempts = 0;

          ws = new WebSocket('ws://192.168.1.127:8080',[]);

          ws.onopen = function () {
            console.log('WebSocket Open');
          };

          ws.onerror = function (error) {
            console.log('WebSocket Error ' + error);
          };

          ws.onmessage = function (e) {
            var rawData = e.data;
            if(rawData.trim().length > 1 &amp;&amp; rawData.trim() != "undefined")
            {
              try {

                var jsonObj = JSON.parse(rawData);
                jsonObj[0]['t'] = jsonObj[0]['t']; // temperature
                jsonObj[0]['p'] = jsonObj[0]['pressure']; // air pressure
                jsonObj[0]['a'] = jsonObj[0]['alt']; // altitude

                dataArr.push(jsonObj);

              } catch(e) {
                  console.log("Invalid JSON:"+rawData.toString());
              }
            }
          };
        }

        // check connection status every 60sec, upto maxReconnectAttemps, try reconnect
        const interval = setInterval(function checkConnectStatus() {
          if (reconnectAttempts++ < maxReconnectAttemps)
          {
            if (ws.readyState !== ws.OPEN) {
               console.log("WS connection closed - try re-connect");
               setupWebSocket();
            }
          }
        }, 60000);

        document.addEventListener("DOMContentLoaded", function() {
            setupWebSocket();
        });

Finally D3.js ( https://d3js.org/ ) is used to render chart as HTML5 / SVG.

D3.js real time barometer chart with WebSocket data provisioning

Source code and documentation can be found here:

Barometer D3.js:
http://bl.ocks.org/steveio/d549b0610fd489e6a09df8f2aa805ad3
https://gist.github.com/steveio/d549b0610fd489e6a09df8f2aa805ad3

ESP32 wifi Arduino MQTT sensor Client:
https://github.com/steveio/arduino/blob/master/ESP32SensorOLEDWifiMQTT/ESP32SensorOLEDWifiMQTT.ino

MQTT to WebSocket NodeJS relay:
https://github.com/steveio/mqttWebSocket