Chapter 3: Building a Weather Station with TensorFlow Lite for Microcontrollers

Nowadays, it is straightforward to get the weather forecast with our smartphones, laptops, and tablets, thanks to internet connectivity. However, have you ever thought of what you would do if you had to track the weather in a remote region with no internet access?

This chapter will teach us how to implement a weather station with machine learning (ML) using the temperature and humidity of the last three hours.

In this chapter, we will focus on dataset preparation and show how to acquire historical weather data from WorldWeatherOnline. After that, we will explain how to train and test a model with TensorFlow (TF). In the last part, we will deploy the model on an Arduino Nano and a Raspberry Pi Pico with TensorFlow Lite for Microcontrollers (TFLu) and build an application to predict whether it will snow.

The goal of this chapter is to guide you through all the development stages of a TF-based application...