Neighborhood Watch

Interactive Heat Map
Application Home Page

Inspiration

Our inspiration for creating Neighborhood Watch stemmed from the different problems we have noticed people are facing in communities all around the world including the COVID-19 pandemic, natural disasters, and injustices committed against others. We wanted to create a virtual space where people can stay informed and inform others of potential dangers in their area in order to foster and maintain the sense of community even during times when we cannot interact physically. Accessibility of this information may help people evacuate faster during wildfires, stay away from certain areas with large infection cases, etc.

What it does

Our web application allows a user to report new case into our database, as well as viewing an interactive heat map of COVID-19 cases.

How we built it

The user interface was developed using the front-end technologies: the React library and the Bootstrap framework. The database contains U.S. COVID-19 cases up until September 26, 2020, hosted in a PostgreSQL instance on Google Cloud. This database communicates with our Django backend server. Python libraries are used to generate the heatmap, as well as COVID-19 data taken https://coronavirus-resources.esri.com/datasets/628578697fb24d8ea4c32fa0c5ae1843_0?geometry=112.752%2C22.406%2C19.764%2C64.233&where=(Confirmed%20%3E%200) .

Challenges we ran into

We had to switch the framework of our backend from .NET Core to Django to support Python scripts that will generate our heatmap. We also had to learn new functionalities in React and how they work.

Accomplishments that we're proud of

We have a backend that is able to generate a heat map and a UI that a user can interact with to generate the heatmap. Our teamwork was also awesome. Our team is also proud of the new knowledge that we have gained working on this project.

What we learned

In doing the research to acquire the necessary data, we learned additional information and statistics regarding COVID-19 such as which regions had the highest infection rates and which areas were able to reduce the number of confirmed cases and further spread of the virus. In working as a team we also all learned new technical skills. Those of us who have front-end experience assisted those who wanted to learn more and those who have more back-end experience assisted those less experienced as well.

What's next for Neighborhood Watch

Neighborhood Watch currently only displays data for COVID-19 incidents but has the capacity to support data for additional incidents in the future as well. Users have the ability to view already reported cases of COVID-19 in the form of a heat map that visually displays the intensity of cases in a county of their choice, informing people of which areas to take extra precautions in or avoid altogether in order to reduce the risk of infection.

Built With

Submitted to

ShellHacks 2020

Created by

I initially created the original .NET Core 3.1 web API that used EF Core to connect to the GCloud Postgres DB. and eventually changed that over to a Django back-end to leverage Python Data Science oriented libraries. I also assisted in helping the team with troubleshooting development environment issues and design how all the services will connect with each other and organized the team progression using a Kanban board in GitHub projects.

Sean Rodriguez
Software Engineer with experience building applications and microservices using C# and JavaScript
I worked primarily on the frontend with React and creating the different modals. I also deployed our database onto Google Cloud.

Anh Nguyen
I created an initial mock up for Neighborhood Watch's user interface using Figma. I also conducted research and provided the team with the data used to develop the map. Additionally, I created the powerpoint that introduces Neighborhood Watch and assisted with the submission of the project.

Sacha Arthurs
I set up react project and implemented user interface components. I analyzed Covid cases data in the US using Python and data science libraries to produce a heat map for a region that user is interested.

Quan Nguyen