Tony studied Mechanical Engineering at the University of Minnesota where he fell in love with 3D design, product development, and prototyping. In his free time, he can often be found woodworking, sewing scarves, tending to houseplants, teaching his cat tricks, or out in the woods camping with friends. He enjoys using his bike to commute, practices yoga to relax, and goes to an ecstatic dance event nearly every weekend. Since Bitcoin’s last big bull-run in late 2017, Tony has been listening to the outcry blaming Bitcoin for being power hungry and wasting computational resources. After learning that most of the electricity consumption goes towards guessing random numbers, he decided to create an alternative. Tony is the founder of Wrfcoin, a cryptocurrency earned by contributing to weather forecasts with raw data or computing resources.
Computational Essay: Native American Flute Design
The goal is to capture data from a personal weather station and have it stored on the Wolfram Blockchain. Receipts from the blockchain are stored in a public databin, so anyone can retrieve the data from the blockchain to analyze. The device used in this project is an AcuRite PRO+ 5-in-1 Weather Sensor, which records temperature, pressure, rainfall, humidity, wind speed and direction. The local results will then be compared with those of the nearest official weather station. Easily connecting such IoT devices and recording data from them are important to the future of weather forecasting and environmental monitoring, which necessarily includes crowdsourcing information from individuals with their own equipment.
Summary of Results
During the Wolfram Summer School, sensor data was charted from a personal weather station against the nearest Internation Civil Aviation Organization (ICAO) weather station, KBED, which is located at the Laurence G. Hanscom Field Airport about 10 miles away. The data from KBED seems to indicate that either the pressure sensor is broken or has far less granularity than the AcuRite Pro+ 5-in-1. Additionally, metrics were created to determine the average distance to the nearest WMO weather station in various countries, and a proximity score was calculated for a location based on the diameters that circumscribe a set number of nearest neighbors.
Future work includes plotting additional weather stations hosted by ICAO and CWOP. Plotting these three datasets together will help determine the geographic areas with the least density of weather stations—where it would make the most sense to install the next weather station. Next steps also include recording multiple personal weather stations into a blockchain and databin such that each contributor gets credit for their contributions and computing weather forecasts augmented with the collected data.