Remote Edge Weather Station
Team 29
Team 29
CS426 Senior Projects | Spring 2022 | University of Nevada, Reno | CSE Department
By Brendan Aguiar, Nicholas Ang, Daniel Beeston, Dalton Tracy, and Kenji Won
Combining embedded systems and application design, Remote Edge Weather Station (REWS) implements a comprehensive and robust weather station system that will meet the expectations of any weather enthusiast. Providing simple design with simple accessibility, a weather enthusiast of any level will be capable of setting and capturing accurate personal weather data from their REWS device and visualizing it in an intuitive and expandable interface. Features like an easy out-of-box (OOB) setup and configuration, diverse data metrics, historical data tracking and visualization, data reports and downloading, and personal data visualization allow for REWS devices to be capable and comprehensive remote weather stations for everyone.
The REWS platform aims to provide a capable weather reporting device for users of any experience level, allow users to configure, visualize, and manage their weather data in a simple and intuitive way, and to create a fully capable weather monitoring system through the internet of things.
The REWS system features an easy-to-use data visualizer application for displaying collected weather data. Using this tool, Users are able view both current and historical data for each collected metric. Historical data is displayed in the form of line graphs which display a sensor's reading over a specified timeframe, along with several statistics. Additionally, users are able to download their data, configure settings, and delete their data from their desktop application. The application also has a dynamic background feature that changes with the latest data available. Data displayed on the visualizer tool is stored on the REWS web server and database, where it can be accessed at any time as long as the visualizer's host device has an internet connection.
The REWS device is an easily configurable weather station capable of collecting data on several different metrics; these metrics include temperature, humidity, wind speed, wind direction, air pressure, air quality, and location. The device is powered by an Arduino Mega 2560 serving as the sensor controller and a Raspberry Pi serving as the main computer for networking capabilities. Once the data is collected, the device then sends the data to the REWS web server where it will be collected for analysis.
The REWS web server is the heart of the operation. The web server was created using Flask, a lightweight Python framework, and is currently hosted on Heroku. The web server uses a PostgreSQL database to store collected data from any REWS device. The web server features a REST API that is used for storing data and servicing requests for both the data visualizer and a device.