Title:

Optimization of Software for Coastal Weather Monitoring

As technology develops and becomes more accessible, it becomes easier to bring scientific equipment to individual or small-scale projects, and collecting weather data is no exception. By utilizing Raspberry Pi’s systems and our existing sensors, we were able to develop a user-friendly, affordable weather station that can be used in classrooms and localized projects to classify regions by their weather. The previous model used in the Ocean Sensing cohort was deployed at Odiorne Point, and failed due to disconnected wires and faulty code. The problem with this model is that it relied on an Arduino base which was outdated and difficult to update as new software replaced old libraries. The goal of this project was to create a successful, more easily used and maintained station to collect specific weather data in various locations. By pivoting to a Pi-based system, we were able to establish a model that has better battery life, a more user-friendly interface, and can be easily improved upon and expanded for future research groups. We found that not only was this system successful, which could not be said about the Arduino, but it was much easier to use and monitor in the field, and allowed for remote access to verify that data was being collected in the first place.

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