Team members: Ryan Lam, Jax Wang, Michael Ng


We were inspired by the rate of deforestation and how quickly we are using our natural resources (wood). As a result, we wanted to help companies cut wood at a sustainable pace so we can sustainably use wood now and in the future/future generations.

What it does

Tree Analyzer reads a dataset and produces graphs to help users (companies) visualize forestry data for the land they own. It also provides advice on which trees to cut by checking our programmed requirements. This allows for better logging practices and preserving more natural resources.

How we built it

We used Django as the backend (API) and regular HTML/CSS/JS as the frontend. The JS in the front end calls our API, allowing the frontend to display new data

Challenges we ran into

  • Plotting 100s of data points on the graph (and aiming to optimize loading time)
  • Getting our JS to connect to the backend and properly get the desired data
  • Cleaning, formatting, sorting, and loading the data from the backend (API)

Accomplishments that we're proud of

  • Getting 4 different charts working and calling 4 different API endpoints
  • Learning how to use JSON, APIs, and getting API requests with JS

What we learned

  • How to use JSON files
  • How to use Chart.JS
  • How to basically (technically) create a GET API

What's next for Tree Analyzer

  • Build a file/database uploaded
  • Use forestry growth modeling
  • AI recommendation tools
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