Testing the application – Looking Ahead into the Future of IoT

We can now test our application. As part of this, we will need to spin up the Flask app and access it from our computer:

On your Raspberry Pi terminal, run the following command on the working directory you have created:
$ python app.py

This may take a few minutes to properly spin up, as the downloading and embedding process takes a while. You then should see that your Flask application is running.

Take note of the IP address of your Raspberry Pi.

Into your web browser on your computer, type the following link: http://<raspberry_pi_ip>:5000.

You should now be able to see a textbox being rendered on the local site. You can then start to try to query, by typing in queries such as the following: Could you tell me more about what to do if I found out that I got a Ransomware?

You will then see that the appropriate section of the document is returned.

With that, you’ve managed to create your first RAG web application! This is a great step forward to exploring one of the most in-demand use cases of generative AI (GenAI) and is set to play a big role in the future of IoT in building smarter devices.

To dive deeper into the integration of IoT and AI technologies, you can build upon the IoT-integrated RAG web app project and expand your knowledge by exploring the following areas:

Voice recognition and text to speech (TTS): Add a voice recognition module and a TTS module to the existing project. This way, users can interact with the RAG application using spoken language, and the assistant can provide spoken responses, creating a more natural and intuitive user experience.

Custom Amazon Bedrock foundational models: Train a custom Amazon Bedrock model to answer domain-specific questions and provide expert insights relevant to your industry or application. This could include creating a model for answering questions about IoT security, energy efficiency, or specific IoT use cases. For this, you will have to explore more with the Amazon Bedrock documentation.

This practical project demonstrates how IoT and AI can work together to provide results based on specific bodies of knowledge. It shows the potential of integrating IoT devices with advanced AI capabilities such as Amazon Bedrock’s foundational models in the context of smart businesses and future IoT applications. By adjusting the prompt variable, you can explore various aspects of IoT, including challenges, best practices, and sustainability. Additionally, you can use the project as a starting point for creating more advanced IoT solutions that integrate AI services such as Amazon Bedrock or ChatGPT to provide valuable information and services to users.