In this project I will show you how to train an image classification model with TensorFlow and deploy it on a Raspberry Pi Zero. The model can count how many fingers you show to the camera. You can use this as a base for further projects, for example to adjust volume of your speakers or lighting in a room based on inputs from 0 to 5.
In this post I am going to detail how to create a real time data pipeline for processing sensor data. First we will connect the sensor and create the code to read it. I will use the DHT22 temperature and humidity sensor on the Raspberry Pi Zero WH. Then we’ll setup the real time data flow with Python and RabbitMQ. Finally we will use Flask and D3.js to display the data in a live dashboard in a browser.
The HC-SR04 is a cheap and easy to use sensor, used to measure distance with ultrasound. It can be used in many projects where you trigger an action based on an object or person entering an area, like an “alarm”, as I showed in my previous post. Also, you often see this sensor as part of more interesting projects such as robots, like this one.