Solo Hacker Winning Project for StemWarriorHacks 2021 Winter Edition
Whistles - ML - a Smart Pressure Cooker Whistle Tracker - powered by machine learning
According to Dhanush, the inspiration to build this project came from his daily tasks at home of turning off the pressure cooker once the rice is cooked. We have all been in similar situations that may have resulted in gulping down some burnt food.
Below are the the inventors own words on how on how he built the project.
I developed this app using Xcode 13.1 and the Swift programming language. I first gathered a decent amount of audio data samples (about #40) capturing pressure cooker whistle sounds, as well as background noises to train an accurate sound classification model using CreateML. Then I performed the machine learning classification in real-time using Apple's CoreML framework and updated the text view to reflect what sound it was currently detecting. I also requested the user to allow access to notifications if they choose that method of alert. The email alert feature was implemented using a restful API that I developed in Python using the Flask framework.
Very inspiring. In the video he explains the magic and elegance of the set of code to solve the problem of detecting the correct sounds of the whistles.
GAR is proud to support StemWarriorHacks and the outstanding project developed by Dhanush. We wish him the best going forward and trust he will continue use his scientific talents to bring extraordinary achievements in engineering, science and the analyzing of sounds!
Congratulations Dhanush and all the 2021 StemWarriorHacks winners!
"If I had asked people what they wanted, they would have said faster horses" - Henry Ford
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