Monthly Archives: May 2019

RFM69 shield library Part2

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Register Dump

Next step was to dump all registers (0x00 RegFifo thru 0x4F RegTemp2) of the RFM69HCW device.

/*
    Copyright ® 2019 May devMobile Software, All Rights Reserved

	 MIT License


	 Permission is hereby granted, free of charge, to any person obtaining a copy
	 of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
	 to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
	 copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:

    The above copyright notice and this permission notice shall be included in all
	 copies or substantial portions of the Software.

    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
	 IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
	 AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
	 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
	 SOFTWARE

	 RegFiFo 0x00 thru RegPacketConfig2 0x3D

*/
namespace devMobile.IoT.Rfm69Hcw.RegisterScan
{
	using System;
	using System.Diagnostics;
	using System.Threading.Tasks;
	using Windows.ApplicationModel.Background;
	using Windows.Devices.Spi;

	public sealed class Rfm69HcwDevice
	{
		private SpiDevice rfm69Hcw;

		public Rfm69HcwDevice(int chipSelectPin)
		{
			SpiController spiController = SpiController.GetDefaultAsync().AsTask().GetAwaiter().GetResult();
			var settings = new SpiConnectionSettings(chipSelectPin)
			{
				ClockFrequency = 500000,
				Mode = SpiMode.Mode0,
			};

			rfm69Hcw = spiController.GetDevice(settings);
		}

		public Byte RegisterReadByte(byte registerAddress)
		{
			byte[] writeBuffer = new byte[] { registerAddress };
			byte[] readBuffer = new byte[1];
			Debug.Assert(rfm69Hcw != null);

			rfm69Hcw.TransferSequential(writeBuffer, readBuffer);

			return readBuffer[0];
		}
	}

	public sealed class StartupTask : IBackgroundTask
	{
		private const int ChipSelectLine = 0;
		private Rfm69HcwDevice rfm69HcwDevice = new Rfm69HcwDevice(ChipSelectLine);

		public void Run(IBackgroundTaskInstance taskInstance)
		{

			while (true)
			{
				for (byte registerIndex = 0; registerIndex <= 0x4F; registerIndex++)
				{
					byte registerValue = rfm69HcwDevice.RegisterReadByte(registerIndex);

					Debug.WriteLine("Register 0x{0:x2} - Value 0X{1:x2} - Bits {2}", registerIndex, registerValue, Convert.ToString(registerValue, 2).PadLeft(8, '0'));
				}

				Task.Delay(10000).Wait();
			}
		}
	}
}

I checked a selection of values from the Debug output and they matched the defaults in the datasheet e.g. 0x07-RegFrfMsb 0xE4, 0x08-RegFrfMid 0xC0, 0x09-RegFrfLsb 0x00, 0x2C-RegPreamble 0x0, 0x2D-RegPreamble 0x03 and 0x4E-RegTemp1 0x01.

Register 0x00 - Value 0X00 - Bits 00000000
Register 0x01 - Value 0X04 - Bits 00000100
Register 0x02 - Value 0X00 - Bits 00000000
Register 0x03 - Value 0X1a - Bits 00011010
Register 0x04 - Value 0X0b - Bits 00001011
Register 0x05 - Value 0X00 - Bits 00000000
Register 0x06 - Value 0X52 - Bits 01010010
Register 0x07 - Value 0Xe4 - Bits 11100100
Register 0x08 - Value 0Xc0 - Bits 11000000
Register 0x09 - Value 0X00 - Bits 00000000
Register 0x0a - Value 0X41 - Bits 01000001
Register 0x0b - Value 0X40 - Bits 01000000
Register 0x0c - Value 0X02 - Bits 00000010
Register 0x0d - Value 0X92 - Bits 10010010
Register 0x0e - Value 0Xf5 - Bits 11110101
Register 0x0f - Value 0X20 - Bits 00100000
Register 0x10 - Value 0X24 - Bits 00100100
Register 0x11 - Value 0X9f - Bits 10011111
Register 0x12 - Value 0X09 - Bits 00001001
Register 0x13 - Value 0X1a - Bits 00011010
Register 0x14 - Value 0X40 - Bits 01000000
Register 0x15 - Value 0Xb0 - Bits 10110000
Register 0x16 - Value 0X7b - Bits 01111011
Register 0x17 - Value 0X9b - Bits 10011011
Register 0x18 - Value 0X08 - Bits 00001000
Register 0x19 - Value 0X86 - Bits 10000110
Register 0x1a - Value 0X8a - Bits 10001010
Register 0x1b - Value 0X40 - Bits 01000000
Register 0x1c - Value 0X80 - Bits 10000000
Register 0x1d - Value 0X06 - Bits 00000110
Register 0x1e - Value 0X10 - Bits 00010000
Register 0x1f - Value 0X00 - Bits 00000000
Register 0x20 - Value 0X00 - Bits 00000000
Register 0x21 - Value 0X00 - Bits 00000000
Register 0x22 - Value 0X00 - Bits 00000000
Register 0x23 - Value 0X02 - Bits 00000010
Register 0x24 - Value 0Xff - Bits 11111111
Register 0x25 - Value 0X00 - Bits 00000000
Register 0x26 - Value 0X05 - Bits 00000101
Register 0x27 - Value 0X80 - Bits 10000000
Register 0x28 - Value 0X00 - Bits 00000000
Register 0x29 - Value 0Xff - Bits 11111111
Register 0x2a - Value 0X00 - Bits 00000000
Register 0x2b - Value 0X00 - Bits 00000000
Register 0x2c - Value 0X00 - Bits 00000000
Register 0x2d - Value 0X03 - Bits 00000011
Register 0x2e - Value 0X98 - Bits 10011000
Register 0x2f - Value 0X00 - Bits 00000000
Register 0x30 - Value 0X00 - Bits 00000000
Register 0x31 - Value 0X00 - Bits 00000000
Register 0x32 - Value 0X00 - Bits 00000000
Register 0x33 - Value 0X00 - Bits 00000000
Register 0x34 - Value 0X00 - Bits 00000000
Register 0x35 - Value 0X00 - Bits 00000000
Register 0x36 - Value 0X00 - Bits 00000000
Register 0x37 - Value 0X10 - Bits 00010000
Register 0x38 - Value 0X40 - Bits 01000000
Register 0x39 - Value 0X00 - Bits 00000000
Register 0x3a - Value 0X00 - Bits 00000000
Register 0x3b - Value 0X00 - Bits 00000000
Register 0x3c - Value 0X0f - Bits 00001111
Register 0x3d - Value 0X02 - Bits 00000010
Register 0x3e - Value 0X00 - Bits 00000000
Register 0x3f - Value 0X00 - Bits 00000000
Register 0x40 - Value 0X00 - Bits 00000000
Register 0x41 - Value 0X00 - Bits 00000000
Register 0x42 - Value 0X00 - Bits 00000000
Register 0x43 - Value 0X00 - Bits 00000000
Register 0x44 - Value 0X00 - Bits 00000000
Register 0x45 - Value 0X00 - Bits 00000000
Register 0x46 - Value 0X00 - Bits 00000000
Register 0x47 - Value 0X00 - Bits 00000000
Register 0x48 - Value 0X00 - Bits 00000000
Register 0x49 - Value 0X00 - Bits 00000000
Register 0x4a - Value 0X00 - Bits 00000000
Register 0x4b - Value 0X00 - Bits 00000000
Register 0x4c - Value 0X00 - Bits 00000000
Register 0x4d - Value 0X00 - Bits 00000000
Register 0x4e - Value 0X01 - Bits 00000001
Register 0x4f - Value 0X00 - Bits 00000000

RFM69 shield library Part1

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Register Read

After building an RFM95 Windows 10 IoT Core C# library I wanted to see if I could source a couple of RFM69HCW hats and write another library. For some applications the RFM69HCW with the variety and number of low-power client devices available plus, its built in payload encryption and addressing make it a better option. For the RFM9X library I purchased several RM9X Raspberry PI Hats but I can only find a couple (May 2019) of suitable RFM69HCW ones.

  • Adafruit RFM69HCW Radio Bonnet 433/868/915MHz USD19.95
  • Seegel Systeme RaspyRFMII EUR17.90

I wanted a lightweight RFM69HCW library which didn’t try to hide how the chip functioned, and in the future could be configured to work with other vendors’ shields.

AdaFruit LoRa 9X/RFM69HCW Radio Bonnet
Seegel Systeme RaspyRFM-II

The first step was to build a basic universal windows platform (UWP) background task to confirm that I could reliably communicate with the AdaFruit shield over the SPI bus by reading a single register value (RegVersion the silicon version specified in the vendor datasheet).

/*
    Copyright ® 2019 May devMobile Software, All Rights Reserved
 
    MIT License

    Permission is hereby granted, free of charge, to any person obtaining a copy
    of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
    copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:

    The above copyright notice and this permission notice shall be included in all
    copies or substantial portions of the Software.

    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
    SOFTWARE

	 CS : CE1
	 RST : GPIO25
	 IRQ : GPIO22 (DIO0)
	 Unused : GPIO23 (DIO1)
	 Unused : GPIO24 (DIO2)
 */
namespace devMobile.IoT.Rfm69hcw.AdafruitSPI
{
	using System;
	using System.Diagnostics;
	using System.Threading;
	using Windows.ApplicationModel.Background;
	using Windows.Devices.Spi;

	public sealed class StartupTask : IBackgroundTask
	{
		private const byte RegVersion = 0x10;

		public void Run(IBackgroundTaskInstance taskInstance)
		{
			SpiController spiController = SpiController.GetDefaultAsync().AsTask().GetAwaiter().GetResult();
			var settings = new SpiConnectionSettings(1)
			{
				ClockFrequency = 500000,
				Mode = SpiMode.Mode0,
			};

			SpiDevice Device = spiController.GetDevice(settings);

			while (true)
			{
				byte[] writeBuffer = new byte[] { RegVersion }; // RegVersion
				byte[] readBuffer = new byte[1];

				Device.TransferSequential(writeBuffer, readBuffer);

				byte registerValue = readBuffer[0];
				Debug.WriteLine("Register 0x{0:x2} - Value 0X{1:x2} - Bits {2}", RegVersion, registerValue, Convert.ToString(registerValue, 2).PadLeft(8, '0'));

				Thread.Sleep(10000);
			}
		}
	}
}

The AdaFruit hat uses chip select 1

/*
    Copyright ® 2019 May devMobile Software, All Rights Reserved
 
    MIT License

    Permission is hereby granted, free of charge, to any person obtaining a copy
    of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
    copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:

    The above copyright notice and this permission notice shall be included in all
    copies or substantial portions of the Software.

    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
    SOFTWARE

    The RaspyRFM is plugged into the Raspberry PI of pin 17-26.

    From the docs for the dual RFM69 mini 
    17 -> 3,3 V
    18 (GPIO 24) -> DIO1 bei Einzelmodul, DIO0 Slave bei Doppelmodul
    19 (MOSI) -> MOSI
    20 -> GND
    21 (MISO) ->MISO
    22 (GPIO 25) -> DIO0
    23 (SCK) -> SCK
    24 (CE0) -> NSS Master
    25 -> GND
    26 (CE1) -> DIO2 bei Einzelmodul, NSS Slave bei Doppelmodul
 */
namespace devMobile.IoT.Rfm69hcw.SeegelSpi
{
	using System;
	using System.Diagnostics;
	using System.Threading;
	using Windows.ApplicationModel.Background;
	using Windows.Devices.Spi;

	public sealed class StartupTask : IBackgroundTask
	{
		private const byte RegVersion = 0x10;

		public void Run(IBackgroundTaskInstance taskInstance)
		{
			SpiController spiController = SpiController.GetDefaultAsync().AsTask().GetAwaiter().GetResult();
			var settings = new SpiConnectionSettings(0)
			{
				ClockFrequency = 500000,
				Mode = SpiMode.Mode0,
			};

			SpiDevice Device = spiController.GetDevice(settings);

			while (true)
			{
				byte[] writeBuffer = new byte[] { RegVersion }; // RegVersion
				byte[] readBuffer = new byte[1];

				Device.TransferSequential(writeBuffer, readBuffer);

				byte registerValue = readBuffer[0];
				Debug.WriteLine("Register 0x{0:x2} - Value 0X{1:x2} - Bits {2}", RegVersion, registerValue, Convert.ToString(registerValue, 2).PadLeft(8, '0'));

				Thread.Sleep(10000);
			}
		}
	}
}

The Seegel hat uses chip select 0

Based on the datasheet the RegVersion (0x10) register the value (ox24) returned by both hats was correct.

'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Threading.Thread.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
Register 0x10 - Value 0X24 - Bits 00100100
Register 0x10 - Value 0X24 - Bits 00100100
Register 0x10 - Value 0X24 - Bits 00100100

Next step is to dump all the registers of the HopeRF module

Grove Base Hat for Raspberry PI Zero Windows 10 IoT Core

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During the week a package arrived from Seeedstudio with a Grove Base Hat for RPI Zero. So I have modified my Grove Base Hat for RPI Windows 10 IoT Core library to add support for the new shield.

Grove Base Hat for Raspberry PI Zero on Raspberry PI 3

The Raspberry PI Zero hat has a two less analog ports and a different device id so some conditional compile options were necessary

namespace devMobile.Windows10IoTCore.GroveBaseHatRPI
{
#if (!GROVE_BASE_HAT_RPI && !GROVE_BASE_HAT_RPI_ZERO)
#error Library must have at least one of GROVE_BASE_HAT_RPI or GROVE_BASE_HAT_RPI_ZERO defined
#endif

#if (GROVE_BASE_HAT_RPI && GROVE_BASE_HAT_RPI_ZERO)
#error Library must have at most one of GROVE_BASE_HAT_RPI or GROVE_BASE_HAT_RPI_ZERO defined
#endif

	public class AnalogPorts : IDisposable
	{
		private const int I2CAddress = 0x04;
		private const byte RegisterDeviceId = 0x0;
		private const byte RegisterVersion = 0x02;
		private const byte RegisterPowerSupplyVoltage = 0x29;
		private const byte RegisterRawBase = 0x10;
		private const byte RegisterVoltageBase = 0x20;
		private const byte RegisterValueBase = 0x30;
#if GROVE_BASE_HAT_RPI
		private const byte DeviceId = 0x0004;
#endif
#if GROVE_BASE_HAT_RPI_ZERO
		private const byte DeviceId = 0x0005;
#endif
		private I2cDevice Device= null;
		private bool Disposed = false;

		public enum AnalogPort
		{
			A0 = 0,
			A1 = 1,
			A2 = 2,
			A3 = 3,
			A4 = 4,
			A5 = 5,
#if GROVE_BASE_HAT_RPI
			A6 = 6,
			A7 = 7,
#endif
		};

The code updates have been “smoke” tested and I have updated the GitHub repository.

Windows 10 IoT Core Cognitive Services Computer Vision API

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This application was inspired by one of teachers I work with wanting to check occupancy of different areas in the school library. I had been using the Computer Vision service to try and identify objects around my home and office which had been moderately successful but not terribly useful or accurate.

I added the Azure Cognitive Services Computer Vision API NuGet packages to my Visual Studio 2017 Windows IoT Core project.

Azure Cognitive Services Computer Vision API library

Then I initialised the Computer Vision API client

try
{
	this.computerVisionClient = new ComputerVisionClient(
			 new Microsoft.Azure.CognitiveServices.Vision.ComputerVision.ApiKeyServiceClientCredentials(this.azureCognitiveServicesSubscriptionKey),
			 new System.Net.Http.DelegatingHandler[] { })
	{
		Endpoint = this.azureCognitiveServicesEndpoint,
	};
}
catch (Exception ex)
{
	this.logging.LogMessage("Azure Cognitive Services Computer Vision client configuration failed " + ex.Message, LoggingLevel.Error);
	return;
}

Every time the digital input is strobed by the passive infra red motion detector an image is captured, then uploaded for processing, and finally results displayed. For this sample I’m looking for categories which indicate the image is of a group of people (The categories are configured in the appsettings file)

{
  "InterruptPinNumber": 24,
  "interruptTriggerOn": "RisingEdge",
  "DisplayPinNumber": 35,
  "AzureCognitiveServicesEndpoint": "https://australiaeast.api.cognitive.microsoft.com/",
  "AzureCognitiveServicesSubscriptionKey": "1234567890abcdefghijklmnopqrstuv",
  "ComputerVisionCategoryNames":"people_group,people_many",
  "LocalImageFilenameFormatLatest": "{0}.jpg",
  "LocalImageFilenameFormatHistoric": "{1:yyMMddHHmmss}.jpg",
  "DebounceTimeout": "00:00:30"
}

If any of the specified categories are identified in the image I illuminate a Light Emitting Diode (LED) for 5 seconds, if an image is being processed or the minimum period between images has not passed the LED is illuminated for 5 milliseconds .

		private async void InterruptGpioPin_ValueChanged(GpioPin sender, GpioPinValueChangedEventArgs args)
		{
			DateTime currentTime = DateTime.UtcNow;
			Debug.WriteLine($"Digital Input Interrupt {sender.PinNumber} triggered {args.Edge}");

			if (args.Edge != this.interruptTriggerOn)
			{
				return;
			}

			// Check that enough time has passed for picture to be taken
			if ((currentTime - this.imageLastCapturedAtUtc) < this.debounceTimeout)
			{
				this.displayGpioPin.Write(GpioPinValue.High);
				this.displayOffTimer.Change(this.timerPeriodDetectIlluminated, this.timerPeriodInfinite);
				return;
			}

			this.imageLastCapturedAtUtc = currentTime;

			// Just incase - stop code being called while photo already in progress
			if (this.cameraBusy)
			{
				this.displayGpioPin.Write(GpioPinValue.High);
				this.displayOffTimer.Change(this.timerPeriodDetectIlluminated, this.timerPeriodInfinite);
				return;
			}

			this.cameraBusy = true;

			try
			{
				using (Windows.Storage.Streams.InMemoryRandomAccessStream captureStream = new Windows.Storage.Streams.InMemoryRandomAccessStream())
				{
					this.mediaCapture.CapturePhotoToStreamAsync(ImageEncodingProperties.CreateJpeg(), captureStream).AsTask().Wait();
					captureStream.FlushAsync().AsTask().Wait();
					captureStream.Seek(0);

					IStorageFile photoFile = await KnownFolders.PicturesLibrary.CreateFileAsync(ImageFilename, CreationCollisionOption.ReplaceExisting);
					ImageEncodingProperties imageProperties = ImageEncodingProperties.CreateJpeg();
					await this.mediaCapture.CapturePhotoToStorageFileAsync(imageProperties, photoFile);

					ImageAnalysis imageAnalysis = await this.computerVisionClient.AnalyzeImageInStreamAsync(captureStream.AsStreamForRead());

					Debug.WriteLine($"Tag count {imageAnalysis.Categories.Count}");

					if (imageAnalysis.Categories.Intersect(this.categoryList, new CategoryComparer()).Any())
					{
						this.displayGpioPin.Write(GpioPinValue.High);

						// Start the timer to turn the LED off
						this.displayOffTimer.Change(this.timerPeriodFaceIlluminated, this.timerPeriodInfinite);
					}

					LoggingFields imageInformation = new LoggingFields();

					imageInformation.AddDateTime("TakenAtUTC", currentTime);
					imageInformation.AddInt32("Pin", sender.PinNumber);
					Debug.WriteLine($"Categories:{imageAnalysis.Categories.Count}");
					imageInformation.AddInt32("Categories", imageAnalysis.Categories.Count);
					foreach (Category category in imageAnalysis.Categories)
					{
						Debug.WriteLine($" Category:{category.Name} {category.Score}");
						imageInformation.AddDouble($"Category:{category.Name}", category.Score);
					}

					this.logging.LogEvent("Captured image processed by Cognitive Services", imageInformation);
				}
			}
			catch (Exception ex)
			{
				this.logging.LogMessage("Camera photo or save failed " + ex.Message, LoggingLevel.Error);
			}
			finally
			{
				this.cameraBusy = false;
			}
		}

		private void TimerCallback(object state)
		{
			this.displayGpioPin.Write(GpioPinValue.Low);
		}

		internal class CategoryComparer : IEqualityComparer<Category>
		{
			public bool Equals(Category x, Category y)
			{
				if (string.Equals(x.Name, y.Name, StringComparison.OrdinalIgnoreCase))
				{
					return true;
				}

				return false;
			}

			public int GetHashCode(Category obj)
			{
				return obj.Name.GetHashCode();
			}
		}

I found that the Computer vision service was pretty good at categorising photos of images like this displayed on my second monitor as containing a group of people.

The debugging output of the application includes the different categories identified in the captured image.

Digital Input Interrupt 24 triggered RisingEdge
Digital Input Interrupt 24 triggered FallingEdge
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Diagnostics.DiagnosticSource.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Collections.NonGeneric.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Runtime.Serialization.Formatters.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Diagnostics.TraceSource.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Collections.Specialized.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Drawing.Primitives.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Runtime.Serialization.Primitives.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Data.Common.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Xml.ReaderWriter.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Private.Xml.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'Anonymously Hosted DynamicMethods Assembly'. 
Tag count 1
Categories:1
 Category:people_group 0.8671875
The thread 0x634 has exited with code 0 (0x0).

I used an infrared motion sensor to trigger capture and processing of an image to simulate a application for detecting if there is a group of people in an area of the school library.

I’m going to run this application alongside one of my time-lapse applications to record a days worth of images and manually check the accuracy of the image categorisation. I think that camera location maybe important as well so I’ll try a selection of different USB cameras and locations.

Trial PIR triggered computer vision client

I also found the small PIR motion detector didn’t work very well in a larger space so I’m going to trial a configurable sensor and a repurposed burglar alarm sensor.

Windows 10 IoT Core Cognitive Services Face API

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After building a series of Windows 10 IoT Core applications to capture images and store them

I figured some sample applications which used Azure Cognitive Services Vision Services to process captured images would be interesting.

This application was inspired by one of my students who has been looking at an Arduino based LoRa wireless connected sensor for monitoring Ultraviolet(UV) light levels and wanted to check that juniors at the school were wearing their hats on sunny days before going outside.

First I needed create a Cognitive Services instance and get the subscription key and endpoint.

Azure Cognitive Services Instance Creation

Then I added the Azure Cognitive Services Face API NuGet packages into my Visual Studio Windows IoT Core project

Azure Cognitive Services Vision Face API library

Then initialise the Face API client

try
{
	this.faceClient = new FaceClient(
			 new Microsoft.Azure.CognitiveServices.Vision.Face.ApiKeyServiceClientCredentials(this.azureCognitiveServicesSubscriptionKey),
											 new System.Net.Http.DelegatingHandler[] { })
	{
		Endpoint = this.azureCognitiveServicesEndpoint,
	};
}
catch (Exception ex)
{
	this.logging.LogMessage("Azure Cognitive Services Face Client configuration failed " + ex.Message, LoggingLevel.Error);
	return;
}

Then every time a digital input is strobed and image is captured, then uploaded for processing, and finally results displayed. The interrupt handler has code to stop re-entrancy and contactor bounce causing issues. I also requested that the Face service include age and gender attributes with associated confidence values.

If a face is found in the image I illuminate a Light Emitting Diode (LED) for 5 seconds, if an image is being processed or the minimum period between images has not passed the LED is illuminated for 5 milliseconds .

private async void InterruptGpioPin_ValueChanged(GpioPin sender, GpioPinValueChangedEventArgs args)
{
	DateTime currentTime = DateTime.UtcNow;
	Debug.WriteLine($"Digital Input Interrupt {sender.PinNumber} triggered {args.Edge}");

	if (args.Edge != this.interruptTriggerOn)
	{
		return;
	}

	// Check that enough time has passed for picture to be taken
	if ((currentTime - this.imageLastCapturedAtUtc) < this.debounceTimeout)
	{
		this.displayGpioPin.Write(GpioPinValue.High);
		this.displayOffTimer.Change(this.timerPeriodDetectIlluminated, this.timerPeriodInfinite);
		return;
	}

	this.imageLastCapturedAtUtc = currentTime;

	// Just incase - stop code being called while photo already in progress
	if (this.cameraBusy)
	{
		this.displayGpioPin.Write(GpioPinValue.High);
		this.displayOffTimer.Change(this.timerPeriodDetectIlluminated, this.timerPeriodInfinite);
		return;
	}

	this.cameraBusy = true;

	try
	{
		using (Windows.Storage.Streams.InMemoryRandomAccessStream captureStream = new Windows.Storage.Streams.InMemoryRandomAccessStream())
		{
			this.mediaCapture.CapturePhotoToStreamAsync(ImageEncodingProperties.CreateJpeg(), captureStream).AsTask().Wait();
			captureStream.FlushAsync().AsTask().Wait();
			captureStream.Seek(0);
			IStorageFile photoFile = await KnownFolders.PicturesLibrary.CreateFileAsync(ImageFilename, CreationCollisionOption.ReplaceExisting);
			ImageEncodingProperties imageProperties = ImageEncodingProperties.CreateJpeg();
			await this.mediaCapture.CapturePhotoToStorageFileAsync(imageProperties, photoFile);

			IList<FaceAttributeType> returnfaceAttributes = new List<FaceAttributeType>();
			returnfaceAttributes.Add(FaceAttributeType.Gender);
			returnfaceAttributes.Add(FaceAttributeType.Age);

			IList<DetectedFace> detectedFaces = await this.faceClient.Face.DetectWithStreamAsync(captureStream.AsStreamForRead(), returnFaceAttributes: returnfaceAttributes);

			Debug.WriteLine($"Count {detectedFaces.Count}");

			if (detectedFaces.Count > 0)
			{
				this.displayGpioPin.Write(GpioPinValue.High);

						// Start the timer to turn the LED off
				this.displayOffTimer.Change(this.timerPeriodFaceIlluminated, this.timerPeriodInfinite);
			}

			LoggingFields imageInformation = new LoggingFields();
			imageInformation.AddDateTime("TakenAtUTC", currentTime);
			imageInformation.AddInt32("Pin", sender.PinNumber);
			imageInformation.AddInt32("Faces", detectedFaces.Count);
			foreach (DetectedFace detectedFace in detectedFaces)
			{
				Debug.WriteLine("Face");
				if (detectedFace.FaceId.HasValue)
				{
					imageInformation.AddGuid("FaceId", detectedFace.FaceId.Value);
					Debug.WriteLine($" Id:{detectedFace.FaceId.Value}");
				}
				imageInformation.AddInt32("Left", detectedFace.FaceRectangle.Left);
				imageInformation.AddInt32("Width", detectedFace.FaceRectangle.Width);
				imageInformation.AddInt32("Top", detectedFace.FaceRectangle.Top);
				imageInformation.AddInt32("Height", detectedFace.FaceRectangle.Height);
				Debug.WriteLine($" L:{detectedFace.FaceRectangle.Left} W:{detectedFace.FaceRectangle.Width} T:{detectedFace.FaceRectangle.Top} H:{detectedFace.FaceRectangle.Height}");
				if (detectedFace.FaceAttributes != null)
				{
					if (detectedFace.FaceAttributes.Gender.HasValue)
					{
						imageInformation.AddString("Gender", detectedFace.FaceAttributes.Gender.Value.ToString());
						Debug.WriteLine($" Gender:{detectedFace.FaceAttributes.Gender.ToString()}");
					}

					if (detectedFace.FaceAttributes.Age.HasValue)
					{
						imageInformation.AddDouble("Age", detectedFace.FaceAttributes.Age.Value);
						Debug.WriteLine($" Age:{detectedFace.FaceAttributes.Age.Value.ToString("F1")}");
					}
				}
			}

			this.logging.LogEvent("Captured image processed by Cognitive Services", imageInformation);
		}
	}
	catch (Exception ex)
	{
		this.logging.LogMessage("Camera photo or save failed " + ex.Message, LoggingLevel.Error);
	}
	finally
	{
		this.cameraBusy = false;
	}
}

private void TimerCallback(object state)
{
	this.displayGpioPin.Write(GpioPinValue.Low);
}

This is the image uploaded to the Cognitive Services Vision Face API from my DragonBoard 410C

Which was a photo of this sample image displayed on my second monitor

The debugging output of the application includes the bounding box, gender, age and unique identifier of each detected face.

Digital Input Interrupt 24 triggered RisingEdge
Digital Input Interrupt 24 triggered FallingEdge
Count 13
Face
 Id:41ab8a38-180e-4b63-ab47-d502b8534467
 L:12 W:51 T:129 H:51
 Gender:Female
 Age:24.0
Face
 Id:554f7557-2b78-4392-9c73-5e51fedf0300
 L:115 W:48 T:146 H:48
 Gender:Female
 Age:19.0
Face
 Id:f67ae4cc-1129-46a8-8c5b-0e79f350cbaa
 L:547 W:46 T:162 H:46
 Gender:Female
 Age:56.0
Face
 Id:fad453fb-0923-4ae2-8c9d-73c9d89eaaf4
 L:585 W:45 T:116 H:45
 Gender:Female
 Age:25.0
Face
 Id:c2d2ca4e-faa6-49e8-8cd9-8d21abfc374c
 L:410 W:44 T:154 H:44
 Gender:Female
 Age:23.0
Face
 Id:6fb75edb-654c-47ff-baf0-847a31d2fd85
 L:70 W:44 T:57 H:44
 Gender:Male
 Age:37.0
Face
 Id:d6c97a9a-c49f-4d9c-8eac-eb2fbc03abc1
 L:469 W:44 T:122 H:44
 Gender:Female
 Age:38.0
Face
 Id:e193bf15-6d8c-4c30-adb5-4ca5fb0f0271
 L:206 W:44 T:117 H:44
 Gender:Male
 Age:33.0
Face
 Id:d1ba5a42-0475-4b65-afc8-0651439e1f1e
 L:293 W:44 T:74 H:44
 Gender:Male
 Age:59.0
Face
 Id:b6a7c551-bdad-4e38-8976-923b568d2721
 L:282 W:43 T:144 H:43
 Gender:Female
 Age:28.0
Face
 Id:8be87f6d-7350-4bc3-87f5-3415894b8fac
 L:513 W:42 T:78 H:42
 Gender:Male
 Age:36.0
Face
 Id:e73bd4d7-81a4-403c-aa73-1408ae1068c0
 L:163 W:36 T:94 H:36
 Gender:Female
 Age:44.0
Face
 Id:462a6948-a05e-4fea-918d-23d8289e0401
 L:407 W:36 T:73 H:36
 Gender:Male
 Age:27.0
The thread 0x8e0 has exited with code 0 (0x0).

I used a simple infrared proximity sensor trigger the image capture to simulate an application for monitoring the number of people in or people entering a room.

Infrared Proximity Sensor triggered Face API test client

Overall I found that with not a lot of code I could capture an image, upload it to Azure Cognitive Services Face API for processing and the algorithm would reasonably reliably detect faces and features.

Windows 10 IoT Core TPM SAS Token Expiry

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This is for people who were searching for why the SAS token issued by the TPM on their Windows 10 IoT Core device is expiring much quicker than expected or might have noticed that something isn’t quite right with the “validity” period. (as at early May 2019). If you want to “follow along at home” the code I used is available on GitHub.

I found the SAS key was expiring in roughly 5 minutes and the validity period in the configuration didn’t appear to have any effect on how long the SAS token was valid.

10:04:16 Application started
...
10:04:27 SAS token needs renewing
10:04:30 SAS token renewed 
 10:04:30.984 AzureIoTHubClient SendEventAsync starting
 10:04:36.709 AzureIoTHubClient SendEventAsync starting
The thread 0x1464 has exited with code 0 (0x0).
 10:04:37.808 AzureIoTHubClient SendEventAsync finished
 10:04:37.808 AzureIoTHubClient SendEventAsync finished
The thread 0xb88 has exited with code 0 (0x0).
The thread 0x1208 has exited with code 0 (0x0).
The thread 0x448 has exited with code 0 (0x0).
The thread 0x540 has exited with code 0 (0x0).
 10:04:46.763 AzureIoTHubClient SendEventAsync starting
 10:04:47.051 AzureIoTHubClient SendEventAsync finished
The thread 0x10d8 has exited with code 0 (0x0).
The thread 0x6e0 has exited with code 0 (0x0).
The thread 0xf7c has exited with code 0 (0x0).
 10:04:56.808 AzureIoTHubClient SendEventAsync starting
 10:04:57.103 AzureIoTHubClient SendEventAsync finished
The thread 0xb8c has exited with code 0 (0x0).
The thread 0xc60 has exited with code 0 (0x0).
 10:05:06.784 AzureIoTHubClient SendEventAsync starting
 10:05:07.057 AzureIoTHubClient SendEventAsync finished
...
The thread 0x4f4 has exited with code 0 (0x0).
The thread 0xe10 has exited with code 0 (0x0).
The thread 0x3c8 has exited with code 0 (0x0).
 10:09:06.773 AzureIoTHubClient SendEventAsync starting
 10:09:07.044 AzureIoTHubClient SendEventAsync finished
The thread 0xf70 has exited with code 0 (0x0).
The thread 0x1214 has exited with code 0 (0x0).
 10:09:16.819 AzureIoTHubClient SendEventAsync starting
 10:09:17.104 AzureIoTHubClient SendEventAsync finished
The thread 0x1358 has exited with code 0 (0x0).
The thread 0x400 has exited with code 0 (0x0).
 10:09:26.802 AzureIoTHubClient SendEventAsync starting
 10:09:27.064 AzureIoTHubClient SendEventAsync finished
The thread 0x920 has exited with code 0 (0x0).
The thread 0x1684 has exited with code 0 (0x0).
The thread 0x4ec has exited with code 0 (0x0).
 10:09:36.759 AzureIoTHubClient SendEventAsync starting
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Net.Requests.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
'backgroundTaskHost.exe' (CoreCLR: CoreCLR_UWP_Domain): Loaded 'C:\Data\Programs\WindowsApps\Microsoft.NET.CoreFramework.Debug.2.2_2.2.27505.2_arm__8wekyb3d8bbwe\System.Net.WebSockets.dll'. Skipped loading symbols. Module is optimized and the debugger option 'Just My Code' is enabled.
Sending payload to AzureIoTHub failed:CONNECT failed: RefusedNotAuthorized

I went and looked at the NuGet package details and it seemed a bit old.

I have the RedGate Reflector plugin installed on my development box so I quickly disassembled the Microsoft.Devices.TPM assembly to see what was going on. The Reflector code is pretty readable and it wouldn’t take much “refactoring” to get it looking like “human” generated code. 

public string GetSASToken(uint validity = 0xe10)
{
    string deviceId = this.GetDeviceId();
    string hostName = this.GetHostName();
    long num = (DateTime.get_Now().ToUniversalTime().ToFileTime() / 0x98_9680L) - 0x2_b610_9100L;
    string str3 = "";
    if ((hostName.Length > 0) && (deviceId.Length > 0))
    {
        object[] objArray1 = new object[] { hostName, "/devices/", deviceId, "\n", (long) num };
        byte[] bytes = new UTF8Encoding().GetBytes(string.Concat((object[]) objArray1));
        byte[] buffer2 = this.SignHmac(bytes);
        if (buffer2.Length != 0)
        {
            string str5 = this.AzureUrlEncode(Convert.ToBase64String(buffer2));
            object[] objArray2 = new object[] { "SharedAccessSignature sr=", hostName, "/devices/", deviceId, "&sig=", str5, "&se=", (long) num };
            str3 = string.Concat((object[]) objArray2);
        }
    }
    return str3;
}

The validity parameter appears to not used. Below is the current code from the Azure IoT CSharp SDK on GitHub repository and they are different, the validity is used. 

public string GetSASToken(uint validity = 3600)
{
   const long WINDOWS_TICKS_PER_SEC = 10000000;
   const long EPOCH_DIFFERNECE = 11644473600;
   string deviceId = GetDeviceId();
   string hostName = GetHostName();
   long expirationTime = (DateTime.Now.ToUniversalTime().ToFileTime() / WINDOWS_TICKS_PER_SEC) - EPOCH_DIFFERNECE;
   expirationTime += validity;
   string sasToken = "";
   if ((hostName.Length > 0) && (deviceId.Length > 0))
   {
      // Encode the message to sign with the TPM
      UTF8Encoding utf8 = new UTF8Encoding();
      string tokenContent = hostName + "/devices/" + deviceId + "\n" + expirationTime;
      Byte[] encodedBytes = utf8.GetBytes(tokenContent);

      // Sign the message
      Byte[] hmac = SignHmac(encodedBytes);

      // if we got a signature foramt it
      if (hmac.Length > 0)
      {
         // Encode the output and assemble the connection string
         string hmacString = AzureUrlEncode(System.Convert.ToBase64String(hmac));
         sasToken = "SharedAccessSignature sr=" + hostName + "/devices/" + deviceId + "&sig=" + hmacString + "&se=" + expirationTime;
         }
   }
   return sasToken;
}

I went back and look at the Github history and it looks like a patch was applied after the NuGet packages were released in May 2016.

If you read from the TPM and get nothing make sure you’re using the right TPM slot number and have “System Management” checked in the capabilities tab of the application manifest.

I’m still not certain the validity is being applied correctly and will dig into in a future post.