NewsThis device detects different household sounds through tinyML

This device detects different household sounds through tinyML

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For those who suffer from deafness or issues with auditory perception keeping track of their surroundings is crucial to remain the safety and security of their home. This issue is what prompted group members Lucia Camacho Tiemblo, Spiros Kotsikos along with Maria Alifieri to create a tiny device that alerts users to specific sounds from the home on their phones.

The team decided to use embedded machine learning to identify the sounds of the surrounding environment, and so they decided to go with the Arduino Nano 33 BLE Sense. After recording numerous examples of various events for example, a conversation making a knock on the doors, watching television, the doorbell and silence and feeding the recordings into an incredibly small model Edge Impulse’s Studio. The model that was created could successfully distinguish between different events for around 90 percent times.

In addition to sending the recognized audio data to an Arduino serial screen, their software also allows the output to be transferred over Bluetooth(r) with low Energy so that a connected phone can receive the information and display the information. The app for mobile devices has three buttons that allow access to an audio list that can be played, as well as certain settings. There is also an additional menu for managing the connection to the Arduino.

Michal Pukala
Electronics and Telecommunications engineer with Electro-energetics Master degree graduation. Lightning designer experienced engineer. Currently working in IT industry.