Azure IoT Hub Integration

Seamlessly connect your Windows IoT devices to Azure IoT Hub for secure communication, device management, and data ingestion. Learn about device twins, direct methods, and message routing.

Key features include:

• Secure device authentication (X.509 certificates, SAS tokens)
• Bi-directional communication (telemetry, commands)
• Device twins for state synchronization
• Cloud-to-device messaging for remote control

Explore the Azure IoT SDKs for Windows to get started.

// Example: Sending telemetry to Azure IoT Hub
#include "azure_iot_hub.h"

void send_telemetry() {
    if (IoTHubDeviceClient_SendEventAsync(iot_hub_client_handle, "{\"temperature\": 25.5}", 0) == IOTHUB_CLIENT_OK) {
        // Telemetry sent successfully
    } else {
        // Error sending telemetry
    }
}

Provisioning Services

Automate the onboarding of your Windows IoT devices at scale using Azure IoT Hub Device Provisioning Service (DPS). This enables zero-touch provisioning for new devices.

• Enrollment groups for managing multiple devices
• Custom allocation policies
• Link to IoT Hub instances

Device Identity and Authentication

Secure your devices from the ground up. Understand how to leverage hardware security modules (TPM) and certificate-based authentication to protect your IoT deployments.

• TPM integration for secure key storage
• Certificate management lifecycle
• Secure boot and trusted execution environments

Secure Updates and Patching

Maintain the security posture of your deployed devices with robust over-the-air (OTA) update mechanisms. Implement secure and reliable firmware and OS updates.

• Signed update packages
• Rollback capabilities
• Delta updates to minimize bandwidth

Advanced Networking Scenarios

Configure and manage complex network topologies for your Windows IoT devices. Support for various communication protocols and network interfaces.

• Wi-Fi, Ethernet, Cellular (LTE/5G)
• Bluetooth and BLE
• MQTT, AMQP, HTTP/S protocols
• Network interface management

Resource Management

Optimize the performance of your Windows IoT applications by effectively managing CPU, memory, and power consumption. Techniques for efficient resource utilization.

• Application lifecycle management
• Background task optimization
• Power management features

Driver Development

Develop custom device drivers for specialized hardware using Windows Driver Frameworks (WDF). Ensure compatibility and optimal performance with your hardware.

• Kernel-mode and user-mode drivers
• Universal Windows Platform (UWP) drivers
• Peripheral driver examples

Running AI/ML at the Edge

Leverage Windows IoT's capabilities to run AI and Machine Learning models directly on your devices. Reduce latency and bandwidth requirements by processing data locally.

• Windows ML API
• ONNX Runtime support
• Integration with Azure AI services

// Example: Using Windows ML for inference
#include "winml.h"

// Load model and bind inputs/outputs
// ...

// Evaluate the model with input data
// ...