Gi flere mennesker muligheten til å se nordlys.
Behovet: Slippe å sjekke 5-6 websider fro data når man skal se etter nordlys.
Løsning: No-cast! Istedenfor Forecast!
What it does
Kombinerer magnetisk feltmåling, værmelding på stedet der og da og lysforurensingskart, for å få oversikt over hvor det er best forhold til å se nordlyset.
How we built it
Backend server source code made with Java. using REST services to gather data from the Norwegian Metrological institute (MET) for weather data, and aurora borealis predictions from NOAA. This data is then analyzed and parsed to create an image that is sent to the frontend to be used as an overlay over the frontend's map.
Currently the forecast API from MET takes a long time to process, as it sends much more data to the backend than what is needed. The long term plan is to change this from the forecast to the nowcast when the nowcast api is extended to include cloud cover data.
The frontend is made with swift and displays a map of Norway. It will request data from the backend server, and sends in the longtitude and latitude coordinates together with the scale of the displayed map, based on which it will receive an image that will be used as an overlay to display the information from the backend server.
Challenges we ran into
Nonexisting APIs, No response from the space observatory in Tromsø. Getting coorrdinate systems to "talk together". Mathematical challenges (inverse Affin etc.) Challenges in regards to designing logo and icons etc.
Accomplishments that we're proud of
A working prototype, despite time limit and network restrictions. Making something that plugs a hole in the market. We took an idea from the drawing board and brought it to life.
We are an international team with students from 5 countries (Austria, Germany, Makedonia, Netherlands and Norway.)
What we learned
There are difficulties in representing geographical data and visualising. Converting can be challenging but rewarding.
What's next for HuntingLights
Switch to Kartverket instead of Apple Maps. Better light pollution data (NVDB streetlights, satelittedata from ESA etc.) Better parcing
Finding sponsors and investors.