Monitor Temperature using Augmented Reality & IoT

Summary

This video demonstrates how to monitor real-time sensor data using augmented reality with Unity, Vuforia, and Blink API. Viewers are guided step-by-step to create an AR project that displays temperature and humidity data from IoT sensors like DHT11 via ESP32 or NodeMCU. The tutorial covers Unity project setup, importing Vuforia, configuring AR cameras, creating image targets, adding input fields and virtual buttons, and scripting the logic to fetch data from Blink API. The final AR experience allows users to press a virtual button to retrieve live sensor data, which can be tested in Unity and exported as an Android APK for real-time AR visualization.

Takeaways

• 😀 The video demonstrates how to monitor real-time sensor data (temperature and humidity) using augmented reality (AR) with Unity and Blink API.
• 😀 Unity is used as the main development platform, and Vuforia Engine is integrated for AR tracking and image target recognition.
• 😀 A target image is created and uploaded to Vuforia Target Manager to serve as the AR reference for displaying sensor data.
• 😀 The AR scene includes a plane with a template image, along with input fields for displaying temperature and humidity values.
• 😀 Input fields are set to 'World Space' render mode and oriented perpendicular to the image target for proper AR visualization.
• 😀 A virtual button is added to the AR scene, which triggers data retrieval from the Blink API when pressed.
• 😀 The C# script (`Click.cs`) handles the logic for reading temperature and humidity data from Blink API and updating the AR input fields.
• 😀 Blink API links include authentication tokens and virtual pin numbers to fetch sensor data from the ESP32 or NodeMCU with DHT11 sensor.
• 😀 The project can be tested directly in the Unity Editor before exporting it to an Android APK for mobile use.
• 😀 The final AR IoT project allows users to see real-time sensor readings in AR, making IoT data visualization interactive and immersive.
• 😀 Careful scaling, rotation, and color adjustments of planes, canvases, and text fields are essential for a clean and readable AR interface.
• 😀 The project can be extended or modified based on user feedback, encouraging experimentation with AR and IoT integration.

Q & A

What is the main objective of the AR with IoT project described in the video?

The main objective is to monitor real-time sensor data, specifically temperature and humidity, over the internet using augmented reality (AR) with the help of Unity and the Blink IoT platform.

Which software and packages are required to start the project?

The project requires Unity for development and the Vuforia Engine package for AR functionality. A Vuforia license key and target image database are also necessary.

How is the AR target image prepared and used in Unity?

The target image is first finalized and uploaded to Vuforia's Target Manager. A database is created for the image, downloaded in Unity format, imported into the project, and used as an Image Target to anchor AR components.

What components are added to the AR target image to display sensor data?

A plane is added to the target image with a template image for visualization. Two Input Fields are added for displaying temperature and humidity values, and their orientation, size, and color are adjusted for clarity.

What is the purpose of the virtual button in the project?

The virtual button allows the user to trigger a data request to the Blink IoT server. Each time the button is pressed, new sensor data is fetched and displayed on the AR interface.

How does the Click.cs script handle sensor data?

The script assigns the input fields to variables, listens for the virtual button press, and then calls functions to fetch temperature and humidity data from the Blink API. The data is then updated in the respective input fields in AR.

How is sensor data retrieved from the Blink IoT platform?

Sensor data is retrieved via API requests to specific virtual pins (v0 for temperature, v1 for humidity) using an authentication token. The data is then returned and displayed in the AR Input Fields.

What steps are taken to ensure the AR interface is readable?

The canvas render mode is set to World Space, the AR camera is assigned, the plane and input fields are correctly rotated and scaled, text size is increased, and background colors are adjusted for readability.

How can the project be tested before exporting to Android?

The project can be tested within the Unity Editor by scaling the target image appropriately, pressing Play, and clicking the virtual button to verify that temperature and humidity data are displayed correctly in AR.

What is the process to export the Unity project to an Android APK?

Go to File → Build Settings → Switch Platform to Android → Click Build → Name the APK file → Save. The generated APK can then be installed on an Android device to test the AR IoT application in real-time.

Which sensors and boards are compatible with this AR IoT project?

The project uses a DHT11 sensor for temperature and humidity data and is compatible with ESP32 or NodeMCU boards. The sensor data is sent to the Blink IoT platform for real-time AR display.

How can the project be extended for more sensors?

Additional sensors can be integrated by creating more input fields in Unity, adding corresponding variables and functions in the Click.cs script, and linking them to new virtual pins in the Blink IoT platform.