Working with radio and Wi-Fi modules, I helped build and program Arduino powered devices that will allow my research group to remotely monitor the environmental conditions of their fields. Adafruit's RadioFruits, radio-enabled Arduino compatible microprocessors, were paired with devices designed to measure environmental data such as particulate matter concentration, location, temperature, and humidity. Some devices were fitted with either a camera for photographing pests or methane sensors for tracking methane emission from cattle. These devices, via their radios, communicated with another RadioFruit paired with an ESP32 Wi-Fi co-processor. This co-processor served as a database so that my group could monitor data remotely.

Alongside the professor and another teaching assistant, this experience allowed me to supervise my student's research projects. I taught students how to solder electronics, prototype circuits on breadboards, program Arduinos, and write in Python. Using these skills, students learned how to write Arduino code that allowed the Arduino to communicate with sensors, to collect data from the sensors, and to store the data. They then used Python to analyze their data. At this stage, I taught students how to interpret their data. This process involved teaching them basics about both analog and digital signal processing, how to think about their data and the implications the data had, and how and what conclusions can reasonably be drawn from the data. From there, I taught students how they can refine their data collection process and how they should present their findings in both a written report and an oral presentation.