How to Build an IoT System with AI Models to Predict Forest Fires in California

In this weather monitoring system, you will learn how to use the DHT22 and BMP180 sensors to collect temperature, humidity, pressure, and altitude data. This data will be sent to a MySQL database for storage via AWS MQTT, allowing for email notifications to users and enabling future research. The Raspberry Pi 4 is utilized in this project as a compact and portable computer to connect the DHT22 and BMP180 sensors. The Raspberry Pi 4 will have AWS-IOT-MQTT installed to transmit data from the Pi to a Restful server. The Restful server, built with FastAPI, will persist the data into the MySQL database and send email notifications to users. This guide will demonstrate the proper use of sensors to construct your IoT system. The cost of the project can be influenced by the price of different sensors, and using reliable sensors can save time during debugging by helping you identify errors in your code rather than in the hardware. The project also involves the use of several libraries on the Raspberry Pi, including AdafruitDHT, AdafruitPythonDHT, AdafruitCircuitPython, and AdafruitPythonBMP. These libraries are essential for retrieving data from the DHT22 and BMP180 sensors. By following this guide, you will understand how to effectively build and manage an IoT weather monitoring system, taking into consideration the cost and reliability of sensors, as well as the interaction of various software libraries.