[Arduino Pro - Nicla Vision] 정품 아두이노 프로 니클라 비젼

Modern elevators are powerful, but they still have a payload limit. Most will contain a plaque with the maximum number of passengers (a number based on their average weight with lots of room for error). But nobody has ever read the capacity limit when stepping into an elevator or worried about exceeding it. In reality, manufacturers build their elevators to a size that prevents an excessive number of passengers. But as a demonstration, Nekhil R. put together a tutorial that explains how to use the Edge Impulse ML platform with an Arduino Nicla Vision board to count elevator passengers. The Nicla Vision is a new board built specifically for computer vision applications — especially those that incorporate machine learning. In its small footprint (less than a square inch), there is a powerful STM32H747AII6 microcontroller, a 2MP color camera, a six-axis IMU, a time of flight sensor, a microphone, WiFi and Bluetooth, and an onboard LiPo battery charger — and it's officially supported by Edge Impulse, making it well suited for ML projects. To build this passenger counter, all you need is the Nicla Vision, a buzzer, an LED, a push button, a power source, and the 3D-printable enclosure. The guide will walk you through how to train and deploy the object detection model, which is what Edge Impulse excels at. It lets you train a model optimized for microcontrollers and then outputs code that is easy to flash onto an Arduino. There are many optimization tricks involved, such as lowering the video resolution and processing the video as grayscale, but Edge Impulse takes care of all of the difficult work for you. After deploying your model to the Nicla Vision, you can mount this device anywhere in an elevator that gives you a view of the whole car. It keeps a running log of passenger counts, which you can visualize later in graphs or as raw data. If the device sees a passenger count that exceeds the set limit, it will flash the LED and sound the