Designing and Building an Inexpensive, Long-Range, Energy-Efficient Weather Station to Improve Local Weather Models Johnnie Johnson, Abhishek Viswanathan CS3720 - Advanced Topics on Internet of Things - Dr. Daniel Mosse School of Computing & Information University of Pittsburgh

Motivation & Background Existing weather stations are either too expensive, limited in range, or require a lot of power. Localised weather data and predictions are hard to come by when existing weather models rely on a few areas that are sampled and then extrapolated to a larger radius. Weather Underground allows and encourages users who own weather stations to upload the data from their weather stations to the WU cloud, and uses a proprietary mathematical model that allows for more fine-tuned local weather prediction. It currently receives data from more than 250,000 personal weather stations, but it is our assumption that this number does not reflect all the people that would like to own a weather station. If users could build their own weather station inexpensively, while also not having to worry about regular maintenance or battery changes, this number could be significantly higher, while also providing greater local weather prediction accuracy. Local weather prediction E

Weather Station Challenges Maintain sensor accuracy in a waterproof environment Range limitations using WiFi or Bluetooth for transmission Expensive Balancing energy usage Data processing

Related Work

Additional Features Aluminum shielding Longer range Basic security Uploading to Weather Underground for citizen science Clearer documentation

Implementation

Personal Weather Station Properties

Future Work - Possible Improvements Defending against replay attacks Better encryption Improve sensor accuracy Rain Gauge, Wind speed, Snow Intensity sensing Longer Battery Life Specialized power-saving modes for best utilization of solar/wind and optimal battery charging Bare-bones Arduino board

Thank you!