eshangillani1

Worked on developing the front-end and back-end of the software. For the front-end, HTML, CSS, and JavaScript was used after choosing a color scheme. For the backend, four key APIs were using including the Vercel Serverless API, Google Street View API, Open-Meteo API, and Leaflet for the maps. The machine learning model (a random forest) was also created and the system shows this data on an interactive map. Key element features include the email list and the recommendations on next steps based on the current prediction.

Worked on further software improvements on the frontend as well as working towards implementation of more cities and locations on the backend, although it isn’t visible on the frontend just yet due to the web code needing to be updated!

Worked on improving clarity, graph accuracy and style consistency throughout the front-end. I also worked on further training the random forest model with data from further back in time (around 6 months rather than the previous 3 using the OpenMeteo API.

Fixed issues with crashes after deployment through Vercel and Railway

Worked on developing a front-end for my Machine Learning model. I used Vercel for deployment and used Node.js for the frontend. Currently, it just shows the latest status, but I plan to add more in the future such as weather statistics and graphs

Worked on adjustments to the structure to make it more accessible and easy to replicate for different cities, as well as being able to expand the number of natural disasters covered. Additionally, worked on getting it to PyPI for the demo

Was working on moving to PyCharm and making basic adjustments for functionality and ease of use. The API pull is still quite slow when running it for the first time, taking around 2-3 minutes, but that seems to be something out of control.

Worked on importing data from the OpenMeteo API into the file and processing it.

I’m working on my first project! This is so exciting. I can’t wait to share more updates as I build.