The Gemini API and the Internet of Things Devices
With artificial intelligence permeating every aspect of life, the Internet of Things (IoT) landscape is undergoing fast change. The development of artificial intelligence (AI) and cloud services has made it possible to link basic microcontrollers with common sensors and actuators to create a wide range of interactive intelligent gadgets. In order to bridge the gap between the digital and physical worlds and address real-world issues that were previously difficult, this blog examine how IoT developers may use the Gemini REST API to build devices that can comprehend and respond to bespoke spoken instructions.
This tutorial will just cover high-level principles to keep things simple, but you can view the whole code sample and device design using the ESP32 microcontroller on GitHub.
From Speech to Action: The Potential of Custom Features and Speech Recognition
It has always proven difficult to incorporate voice recognition into IoT devices, particularly those with little memory. Although you can run simple models to identify keywords using tools like LiteRT for Microcontrollers, developers can benefit from human language as a far more comprehensive and sophisticated input. By offering a robust, cloud-based solution that can comprehend a large variety of spoken language even across languages from a single tool and decide what to do with an embedded device depending on user input, the Gemini API makes this process easier.
These features depend on the Gemini API’s capacity to process and decipher audio data from an Internet of Things device and identify the subsequent action the device ought to take by following these steps:
- Audio capture: A spoken utterance is recorded by the Internet of Things gadget that has a microphone.
- Audio encoding: Speech is converted into a format that can be sent over the internet. Analogue signals are converted to WAV audio in the official example above, and then to a base64 encoded text for the Gemini API.
- API request: A REST API call is made to the Gemini API to send the encoded audio. This call contains instructions, like asking for the spoken command’s text or telling Gemini to choose a pre-programmed custom function (like turning on lights). You must include function definitions, including names, descriptions, and parameters, in your request JSON if you’re using the Gemini API’s function calling capability.
- Processing: The AI models in the Gemini API examine the audio that has been encoded and choose the best answer.
- The IoT device receives information from the API in the form of a text response with additional instructions, a transcript of the audio, or the next function to call.
For instance, let’s think about using voice commands to change the colour and turn on/off an LED. Toggling the LED and changing its colour are two functions that it can define. It can accept any RGB value between 0 and 255, which gives us over 16 million different options, rather than restricting the colour to a predetermined range.
Despite being a highly simplified example, this one does provide many useful advantages for IoT development:
- Improved user experience: Even for low-memory devices, developers can readily incorporate voice input, making interaction more natural and intuitive.
- Command processing made simpler: With this configuration, there is no need for intricate parsing logic, such as attempting to deconstruct every spoken command or waiting for more intricate manual inputs to determine which function to execute next.
- Dynamic function execution: Gemini AI makes gadgets more dynamic and able to do complex tasks by automatically choosing the right action based on user intent.
- Contextual understanding: The Gemini API can comprehend more general statements like “it’s dark in here!” or “give me some reading light” or “make it dark and spooky in here” to provide users with an appropriate solution without them having to specify it, whereas older speech recognition patterns required a structure similar to “turn on the lights” or “set the brightness to 70%.”
With the Gemini API, developers can combine function calling and audio input to construct Internet of Things devices that can react intelligently to spoken commands.
Turning Ideas into Reality
There is a lot more that can be done to develop incredible and practical intelligent devices, even while audio and function calling are crucial tools for integrating AI into IoT devices. Among the possible directions for investigation are:
- Smart home automation: Voice-control lighting, appliances, and other devices for convenience.
- Robotics: Verbally command robots or submit photographs or video to the Gemini API for navigation, task execution, and interactivity to automate repetitive tasks and aid in various situations.
- Industrial IoT: Improve specialised equipment and machinery to boost output and lower danger for those who depend on them.
