Inspiration
Local news story about a nearby beach, North Beach. Residents and business owners have noticed a significant decrease in the beach over many years. One resident states they remember when the beach went out "100 feet." Others mentioned their worry of the sea going up and towards the sidewalk. In other places, earlier this year, California had experienced massive changes to its coast as the coastal cliffs eroded due to El Niño storms. Additionally, Hawaii experienced similar issues with its coasts in 2022.
What it does
The Coastal Watcher web page, in its current state, monitors data from 2000 to 2024 while comparing updated wave and sea-level forecasts with recent conditions and historical shoreline change to flag beach areas that may need closer review. However, the web page does not constantly monitor these changes and indices. Instead, we would have to rerun our Python script to gather the updated data and update the website data.
How we built it
We started with the idea of building a website so we can warn residents and local officials of projected (End-Point Rate and Linear Regression Rate) erosion and accretion. We used ChatGPT 6 Luna to gather data from data sources, including APIs, to create a Python script so we could pull the data as files onto our local device. Then we exported the data into Replit to make a web page that visualized the results of the data. The results display the projected rates. From the ESP32s3 circuit, we exported data such as water height, wind, ground movement, weather, and device output. This is then compared to our data sets on the web page.
Challenges we ran into
We faced issues related to connecting the ESP32s3 to our computers. We faced issues with token and usage limits on LLMs. We faced issues while attempting to figure out how to gather data from APIs, while also trying to figure out which APIs were important to us.
Accomplishments that we're proud of
We built a website from scratch, we got the datasets from the APIs, and then we put together the ESP32-S3 circuit.
What we learned
We learned about APIs, how to use LLMs, and how to work with ESP32-S3 boards.
What's next for TideSync
We could develop the coastal weather system to constantly monitor the data for the beach.
Built With
- apis
- auduinoide
- claude
- esp32s3
- python
- replit
