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arduino C/C++ circuits Coding Embedded esp32 esp8266 expressif Internet of Things microcontrollers

ESP-32 : How to write multi-threaded application with priority, CPU core affinity, asynchronous non-blocking event driven loop.

Espressif Systems Shanghai launched the game changing low cost ESP-8266 microcontroller in 2014 – a key enabler for embedded Internet of Things (IOT) development.

Internet of Things (IOT)

Adding WiFi 802.11 and Bluetooth LE wireless connectivity to system on a chip (SoC) product costing roughly price of a cup of coffee meant innovators and micro electronics DIY enthusiasts could easily interface edge smart sensor or legacy hardware systems with cloud or mobile devices.

The successor chip ESP-32 (launched 2016) introduced Xtensa LX6 processor and FreeRTOS (a real time operating system (OS) for embedded) – enabling multi-threaded applications running on multi core CPU architecture.

To add context, many even relatively complex tasks especially automation, can be run on tiny embedded 8 bit processor such as Arduino. More complex applications, video, audio signal processing, image recognition or AI require much more compute power.

ESP-32 in the eco-system sits between Arduino and more powerful systems Raspberry Pi, Windows or Embedded Linux.

Sounds great, but how does it work in practice?

ESP8266

In this sketch ( https://github.com/steveio/arduino/tree/master/ESP32GPSMultiTask ) we assemble a UBLOX GPS data logger with an SD card internal storage, LoRaWAN wireless relay and an OLED display.


The goal is to demonstrate running 4 separate non-blocking tasks concurrently using FreeRTOS to schedule tasks, suspend, interrupt, queue and share data in thread-safe way with mutex semaphore locks.

Let’s take a look at the code…. concentrating on FreeRTOS multi-core multi-thread potential, rather than peripherals / sensors.

Data Structures, Multi-thread Semantics & Setup()

First, a struct to encapsulate core data model message (GPS data):

// GPS position data
struct XPosit
{
float Lat;
float Lon;
float Alt;
float Course;
float Speed;
} xPosit;

Next two semaphores to serialise reading and writing tasks to ensure data consistency:

// Semaphores to lock / serialise data structure IO
SemaphoreHandle_t sema_GPS_Gate;
SemaphoreHandle_t sema_Posit;

Then a pointer queue for passing messages between threads / tasks:

// GPS position data queue
QueueHandle_t xQ_Posit;

Here is the related setup():

sema_GPS_Gate = xSemaphoreCreateMutex();
sema_Posit = xSemaphoreCreateMutex();

xSemaphoreGive( sema_GPS_Gate );
xSemaphoreGive( sema_Posit );

Now let’s define 4 tasks:

// task handles
static TaskHandle_t xGPSTask;
static TaskHandle_t xLoRATask;
static TaskHandle_t xSDWriteTask;
static TaskHandle_t xOLEDTask;

// hexadecimal notification code
define GPS_READ_BIT 0x01
define LORA_TX_BIT 0x02
define LORA_RX_BIT 0x04
define SD_WRITE_BIT 0x06
define OLED_BIT 0x08

ISR / Interrupt for Asynchronous Non-Blocking Event Loop

The system will be driven by a periodic ISR timer raising an interrupt calling a handler routine running & managing tasks.

Keeping loop() empty results in non-blocking program execution, no waiting on calls to delay() in main routine – and we only need to call ISR once every ten seconds to read GPS (rather than polling loop()) – which is better for low power consumption.

Under the hood FreeRTOS works in the same way:

> FreeRTOS implements multiple threads by having the host program call a thread tick method at regular short intervals. The thread tick method switches tasks depending on priority and a round-robin scheduling scheme.
( https://en.wikipedia.org/wiki/FreeRTOS#References )

With a task based modular event driven architecture, failure of one task – if write to SD card task blocks or fails because there is no storage card present), other tasks – reading GPS messages, LoRaWAN radio transmit continue.

// ISR timer
hw_timer_t * timer = NULL;
portMUX_TYPE timerMux = portMUX_INITIALIZER_UNLOCKED;
unsigned long isrCounter = 0;

ISR Handler Function (Main control routine, replaces loop()):

// ISR Interupt Handler
void IRAM_ATTR fLoRASendISR( void )
{
portENTER_CRITICAL_ISR(&timerMux);

// Main program routine here ..

portEXIT_CRITICAL_ISR(&timerMux);
}

In setup() we schedule ISR timer:

// Configure Prescaler to 80, as our timer runs @ 80Mhz
// Giving an output of 80,000,000 / 80 = 1,000,000 ticks / second
timer = timerBegin(0, 80, true);
timerAttachInterrupt(timer, &fLoRASendISR, true);

// Fire Interrupt every 10s (10 * 1 million ticks)
timerAlarmWrite(timer, 10000000, true);
timerAlarmEnable(timer);

FreeRTOS Task (Thread) Setup

Next in setup() we describe & initialise tasks, specify which CPU core they should run on, their priority and a few other details

// create a pointer queue to pass position data
xQ_Posit = xQueueCreate( 15, sizeof( &xPosit ) );

Serial.print("Start Task fGPS_Parse() priority 0 on core 0");
xTaskCreatePinnedToCore( fGPS_Parse, "fGPS_Parse", 1000, NULL, 0, &xGPSTask, taskCore0 );
configASSERT( xGPSTask );


Serial.println("Start Task fSD_Write() priority 4 on core 1");
xTaskCreatePinnedToCore( fSD_Write, "fSD_Write", 1000, NULL, 4, &xSDWriteTask, taskCore1 ); // assigned to core 1
configASSERT( xSDWriteTask );

Serial.println("Start Task fLoRA_Send() priority 3 on core 1");
xTaskCreatePinnedToCore( fLoRA_Send, "fLoRA_Send", 1000, NULL, 3, &xLoRATask, taskCore1 ); // assigned to core 1
configASSERT( xLoRATask );

Here’s how to have a task start and wait suspended pending a notification. LoRaWAN transmit task starts and waits until read GPS notifies of new message to send; no need to constantly run radio draining battery or poll the message queue.

for( ;; )
{
/* block until task notification */
xResult = xTaskNotifyWait( LORA_TX_BIT,
                     ULONG_MAX,        /* Clear all bits on exit. */
                     &ulNotifiedValue, /* Stores the notified value. */
                     portMAX_DELAY );  /* Block indefinately */

if( xResult == pdPASS ) 
{

Executing FreeRTOS threads : ISR Main Routine

In main ISR program loop, here’s how to notify tasks:

BaseType_t xHigherPriorityTaskWoken = pdFALSE;

/* Notify (trigger) Read GPS
xTaskNotifyFromISR( xGPSTask,
                   GPS_READ_BIT,
                   eSetBits,
                   &xHigherPriorityTaskWoken );

/* Notify LoRA send task to transmit by setting the TX_BIT */
xTaskNotifyFromISR( xLoRATask,
                   LORA_WRITE_BIT,
                   eSetBits,
                   &xHigherPriorityTaskWoken );

Inter process Communication (IPC): Semaphore Mutex Locks

Concurrency & data consistency in real time and multi threaded systems requires care to ensure serial ops – a write by one thread to a data struct for example must not corrupted by another concurrent thread.

The classic answer to this is locks – mutex, semaphores. A thread requests obtains & takes a lock and other tasks block (wait, retry). The lock is revoked only when lock holding task completes or rolls back.

Here is how it’s done in FreeRTOS:

   if ( xSemaphoreTake( sema_GPS_Gate, xTicksToWait0 ) == pdTRUE )
{
 if ( xSemaphoreTake( sema_Posit, xTicksToWait1000 ) == pdTRUE )
    {
      xPosit.Lat = gps.location.lat();
      xPosit.Lon = gps.location.lng();
      xPosit.Alt = gps.altitude.meters();
      xPosit.Course = gps.course.deg();
      xPosit.Speed = gps.speed.kmph();

      xSemaphoreGive( sema_Posit );
    }


    if ( xSemaphoreTake( sema_Posit, xTicksToWait1000 ) == pdTRUE )
    {
      Serial.println("xQueueSend()");
      pxPosit = &xPosit;
      xQueueSend( xQ_Posit, ( void * ) &pxPosit, ( TickType_t ) 0 );  
      xSemaphoreGive( sema_Posit );
    }

    xSemaphoreGive( sema_GPS_Gate );
  }

FreeRTOS : Message Queue

Those interested in using Queue’s (a sized FIFO pointer linked buffer) to pass data between tasks should consult the API reference:

https://www.freertos.org/a00018.html

// Examples:

// Writing
if ( xSemaphoreTake( sema_Posit, xTicksToWait1000 ) == pdTRUE )
        {
          pxPosit = &xPosit;
          xQueueSend( xQ_Posit, ( void * ) &pxPosit, ( TickType_t ) 0 );  
          xSemaphoreGive( sema_Posit );
        }

// Reading..
struct XPosit xPosit, *pxPosit;
  
 if( xQueueReceive( xQ_Posit,
                         &( pxPosit ),
                         ( TickType_t ) 10 ) == pdPASS )
      {

Conclusion

Espressif changed the game in 2014 with ESP8266 – bringing WiFi & Bluetooth to Arduino’s eco-system of low cost interoperable sensors & components – the internet of things (IOT) long promised since at least 1980s as “smart home” concept finally came of age.

Modern mobile devices and laptops are now so incredibly complex as to be virtually indecipherable, especially at hardware / OS level – to most people, even those within IT industry.

Arduino made it possible for students, DIY enthusiasts, makers & researchers to work with Microcontrollers in a way that is relatively simple, comprehensible and fun. No longer do you necessarily need a PhD, work for tech giant or own a CPU manufacturer to build a micro-electronics project.

By adding WiFi, Bluetooth & LoRaWAN wireless, Espressif opened door to new information age of cloud connected smart sensor & control devices. IOT smart home devices & solutions from Amazon AWS and Google (Matter) are already available in marketplace.

But the option endures – those who wish to can make their own or projects or use a component approach to Internet connect existing machines.

It remains to be seen in decades to come whether people use this tech for good, to benefit people, to make things better; or for nefarious activities – stalking, tracking, surveillance; or worse AI enabled weapons…

(my plan for this prototype was to add 6 axis accelerometer, attach prototype to a stunt kite, aquire some flight input data, create some cool real time web visualisations and explore some more Python SciPi, Mathplotlib & Pandas libraries (alas the prototype proved too fragile to get off the ground).

Anyway hope this tutorial helps you, it took me 30 years to even vaguely understand micro electronics hardware, multi-threading, c++…

Categories
arduino C/C++ circuits Coding Embedded esp32 expressif Internet of Things microcontrollers MQTT sensors weather station WebSockets

SparkFun Weather Sensor Kit

Wind and Rain sensor kit newly arrived from SparkFun Electronics to upgrade an Arduino Weather Station project.

SparkFun Weather Sensor Kit, DIY prototypes, Arduino Weather Station

Also pictured are earlier DIY prototypes – a childrens bee wind spinner with hall effect sensor to count rotations, an anemometer made from recycled plastic packaging utilising a IR Led optical rotary encoder and a wind vane with eight fixed directional magnetic switches.

( more here: http://www.steveio.com/2020/07/21/weather-station-wind-vane-history-science/ and http://www.steveio.com/2020/07/21/weather-vane-hall-sensor-magnetic-rotary-encoder/ ).

Bee Windmill Anemometer with ESP32 LoRa Transmitter running on single 3.3v Li-Ion cell.
8 Durection WInd Vane with magnetic hall sensor array and WebSocket TCP web browser interface.
ESP8266 Anemometer with optical IR Led sensor, wifi connectivity and D3.js websocket provisioned UI.

( Code for these projects can be found on GitHib. )

Weather station projects are a popular accessible introduction to microelectronics; a microcontroller and sensors can be found at low cost, modular hardware design results in easy assembly and open software platforms like Arduino IDE streamline packaging and deployment of code to devices.

Analysing real time or historical time series data, from weather sensors is a lot of fun. Frameworks like R Project for Math Stats: https://www.r-project.org/ ) and Python, Pandas, Numpy & Mathplotlib provide implementations of most alogirithms and convenient data structures for importing & manipulating data.

Techniques and methods are transferable and can be applied to other domains or ontologies – finanicial, accounting data for example.

SparkFun offer an OEM Wind & Rain sensor kit manufactured by Shenzen Fine Offset Electronics, China.

With advent of 3d modelling & printing it is also feasible for an enthusiast to design and fabricate via a 3d printer custom sensor components, perhaps using template models downloaded from repos like ThingiVerse.

In competition marine OpenWind are defining what smart network connected sensors can achieve utilising Bluetooth LE to make near real time wind data available on smartphone.

Assembled SparkFun Weather Sensor Kit

Ideal for enthusiast or educator SparkFun Weather kit comes wihout circuitry,  microcontroller or software.  An add-on PCB designed for use with  Arduino / ESP32 can be purchased or Datasheet Technical Specs provide reference sensor circuit designs, not significantly complex due to use of magnetic reed switch and variable resistance technology.

MCU Sensor Control & Relay Unit – IP67 Weather Proof Enclosure, ESP32 TTGO LoRa microcontroller, light, temperature and air pressure sensors.

Traditionally 433MHz RF has been used for base station to transmitter devices. A popular project is to use Arduino, a cheap 433Mhz receiver and a library to read data from a commercial weather station designed for use with manufacturers display, enabling this data to be provisioned to the cloud.

For data transmission non GPRS (cellular) options include Bluetooth LE (range ~100 metres) or LoRa (Long Range Low Power Network – range between 300 – 10km depending on antenae) offering cableless wireless connectivity allowing remote sensor situation with no associated network costs.

At data layer WebSockets and MQTT for IOT devices are challenging serial protocols as defacto lightweight, reliable & easy to implement transport relays.

Apart from range and connectivity goals of low power consumption for efficient and long battery running time combined with solar charging enable devices to run standalone for long periods.

Is a single 3.3v Li-Ion Battery Cell Sufficient? TP405 Charging Module & Solar Panel

Weather Stations have applications beyond meteorology in smart agriculture, industrial, safety monitoring and for wind or wave based leisure pursuits. 

Assembling DIY Arduino Mega Weather Station v1.0

More generally Internet of things wireless networked smart sensor platforms can be used for many purposes and combined with AI and Machine Learning algorithms useful insight and patterns within data can be analysed, classified and predicted. 

SparkFun Smart ETextiles & Conductive Thread Kit

Personally, I really enjoyed SparkFun Arduino LilyPad e-textile, smart fabrics and conductive thread kit, so looking forward to now spinning up the Weather Station sensors!

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