Content for Arduino Nano 33 BLE

4 Legged Robot and Head Swing Robot

“Robot using Arduino Nano 33 BLE Camera Shield. I will introduce a robot that uses Arduino Nano 33 BLE OV7670 Camera Shield. A robot that swings its head using two servos and a four-legged robot that uses four servos. In …

OV7670 Camera Shield VerII FPGA Servo Controller

“An FPGA implemented smooth servo controller for Arduino Nano 33 OV7670 Camera Shield. These two servos is controlled by the servo controller using FPGA (Field programmable gate array). The video shows Panning operation and speed movement with deceleration stop. The …

Controlling Traffic Lights with Micro Speech

“A TensorFlow Lite Micro Speech model that detects wake words and turns on a different coloured LED light to emulate traffic lights. Introduction and Motivation Machine learning typically involves lots of computing power, and these are usually in the form …

GPS and AHRS Data Logger

“Real-time position data and AHRS data logged to a mSD card. GPS and AHRS data logger on SD card. Connecting Arduino Nano 33 BLE Sense, MKR GPS Shield with ublox 8M GPS and mSD card adapter. Connect the datalogger to …

Arduino Nano 33 BLE OV7670 Camera Shield

“Embedded machine vision board, make your robotics ML enable. Arduino Nano 33 BLE processing capacity is moderately high for the low power consumption embedded system. Since it has many sensors on board, it seems to be very fun to run …

Sound Spectrum Visualizer with Arduino Nano 33 BLE

“Visualize sound frequencies spectrum with an OLED 128x32 display, Arduino Nano 33 BLE and an electret microphone amplifier (MAX9814). See how a bar graph respond to music and sound in a little OLED display. Lowest frequencies toward the left end …

TinyML Keyword Detection for Controlling RGB Lights

“Train a TensorFlow model to recognize certain keywords and control an RGB light strip using an Arduino Nano 33 BLE Sense. The Premise Machine learning at the edge is extremely useful for creating devices that can accomplish “intelligent” tasks with …

Robot Fall Detection with Edge Impulse

“How do you tell the difference between a fall and a sudden, normal movement? Train a machine learning model to detect when a fall occurs. The Idea Imagine creating a simple robot that can navigate around a room on its …

Determining a Plant’s Health with TinyML

“Scan the leaves of a plant with an Arduino Nano 33 BLE Sense and train a model to detect if it’s diseased. Just like humans, plants can become diseased too. And just like how you might develop a rash …

Spectrino: TinyML Arduino & IoT Based Touch-Free Solutions

“Spectrino - Arduino devices that can be implemented on a wide spectrum of touch-free tinyML based housing and society systems. The pandemic has introduced a constraint to social interaction: distance. Considering this factor of risk, countries all over the world have …