Content for Arduino Nano 33 BLE Sense

How to monitor a beehive with Arduino Nano 33BLE (bluetooth)

“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 …

Water pH Monitoring for Hydroponic Plant

“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 …

Battery Life Cycle Predictor Powered by Edge Impulse

“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 …

Arduino Nano BLE 33 Sense Game Controller

“I made this game controller by using Arduino Nano BLE 33 Sense which has onboard proximity sensor. 1) In this project I used the Arduino Nano BLE 33 Sense which has onboard proximity sensor 2) First upload the Serial.ino …

Table Tennis Bat With Machine Learning AI

“Since the pandemic started, me and my housemates bought a Table Tennis table and started playing a lot of Table Tennis. I made this project so that I could monitor and test how well I perform my shots based on …

Snoring Guardian

“Using a Tensorflow Lite Micro model this edge device keeps an ear out and vibrates if you are snoring. Overview Snoring is estimated to affect 57% of men and 40% of women in the United States. It even occurs in …

Hearing Substitution Using Haptic Feedback

“Exploring AAC to substitute hearing through Neosensory Buzz’s haptic feedback for deaf parents to connect to their kids. Deaf People Parenting Hearing Children Ever wonder how difficult it is for deaf people parenting hearing and speaking children, since infant …

Welcome to CurrentSense-TinyML

“CurrentSense-TinyML is all about detecting microcontroller behaviour with current sensing and TinyML. Basically we are trying to work out what is happening on a target PCB. This work is inspired by prior work I have done, as well as the …