Inspiration
Our team was inspired to develop RescueRadar by the need of more effective and faster disaster response as a result of Hurricanes Milton and Helene.
What it does
RescueRadar uses data analysis on input user responses to predict the conditions of neighboring households according to the responses that it has. Once it has the predictions, the locations will show up on the map for first responders to see.
Challenges we ran into
We faced some challenges during the data processing. At first, we want to use clustering method but after consulting with a mentor, we realized that clustering will only replicate the user inputs and will not produce significant results. We decided to use the bayesian network that can provide more powerful and responsive tool for disaster response. However, still during the process we had to learn a lot of new things and had some problems with the debugging.
Accomplishments that we’re proud of
We’re proud that even though for most of our team it was the first hackathon and we used an advanced idea of using the bayesian network to analyze our data.
What we learned
Since, this hackathon is new for most of us, we learned a lot of new things when trying to code. We divided each member to do specific task such as the web design, the user input fetching, producing the resul, and applying the bayesian network. Each of us learned a lot of new skill on our own as well as get new insight about machine learning. Moreover, we also learned how important is teamwork and coordination in a team to avoid conflict trouble. Communication is clearly the key for the team’s success. Through a solid communication of our ideas we are able to create creative innovations and create this project.
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