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“In order to prevent colony collapse syndrome, we have created an autonomous embedded system to help beekeepers During our 4th year at Polytech Sorbonne, we took part in the conception and set-up of a monitoring embedded system applied on hives …

“This project aims to monitor remotely the evolution of a bee colony, thanks to a connected system equipped with sensors of all kind. Story Since the end of the 90’s, a phenomenon known as Colony Collapsse Disorder, among honey …

“An automatic suspension adjustment on a bicycle that able to understand the character of the terrain and the activities of the rider. In this project we use data from the motion sensor on the Arduino Nano 33 BLE Sense which …

“Fall detection prototype with Arduino clients, Raspberry Pi server and Machine Learning. “I’m going, down, down, down, down, down. Yes, I’ve got my feet in the window. Got my head on the ground” Going down (Freddie King) Falls …

“Introducing GetFit, your ultimate health and workout partner. GetFit is an easy-to-use, teachable fitness tracker with the capability of detecting an endless variety of exercises. Powered by Arduino Nano 33 BLE Sense and Edge Impulse, it is a completely open-source …

“Is easy to run large Machine Learning models in the cloud with large computational and memory resources. What about in the Arduino Nano? Deep Learning Workflow In this project, the steps followed to implement our person detection application are the …

“This project can automatically classify three different musical genres (i.e., classical, metal, and reggae) from device-playing music files. Dataset Music can be classified into genres in a variety of ways, including rock, pop, religious, and secular music. This project …

“You have a beehive and you want to optimise your interventions ? Checkout our project where we embed sensors in the beehive. Our team was led to rub shoulders with beekeepers and after few exchanges some issues appeared. Indeed, beekeepers do …

“Sense the water pH of a hydroponic plant with Arduino Nano 33 BLE Sense and determine if it’s right using an Edge Impulse trained model. Introduction I’ve had a hydroponic plant for two years now, and everything went …

“A TinyML model to predict the Lithium Ion battery’s life cycle within shorter time using Edge Impulse. To predict the Life cycle of Lithium Ion battery, there are many methods are available. one of the common method is by …