Danger Tracker

Image of our application

Inspiration

There are many great places to visit in San Francisco, and there's something for everyone. For people who love nature and science, there's the California Academy of Sciences. For sports fans, Oracle Park is perhaps the most beautiful ballpark in the USA. However, some of these hotspots are near rather unsafe areas of the city. Our hack aims to give users a means to prepare and avoid such danger.

What it does

The Danger Tracker Application utilizes Google Maps API to identify and alert users to nearby dangers and hazards. Whether it's navigating through unfamiliar neighborhoods, avoiding road closures, or steering clear of natural disaster zones, our platform provides critical, up-to-the-minute information to keep users safe.

How we built it

We built Danger Tracker by integrating React.js and Next.js for a responsive and intuitive user interface. Google's Maps JavaScript API, Places API, and Roads API were instrumental in developing the mapping functionalities. MongoDB was utilized for storing and querying data efficiently, enabling us to handle real-time information updates seamlessly.

Challenges we ran into

Some issues we had surrounded Google APIs somwhat limited documentation. For example there was very little information regarding Place ID and how we can retrieve details from a location based on an ID. We also had some basic workflow and devops issues that resulted from no cleear protocol when using version control in a collaborative form.

Accomplishments that we're proud of

For a project worked on by relative beginners/medium experience developers, we were able to get a minimum viable product out in a somewhat timely fashion. This project gave us a lot of experience in the mechanics of Hackathon workflow and timelines. It also helped bring out our collaborative skills to the forefront and challenge them.

What we learned

Throughout the development, we gained invaluable insights into processing and visualizing real-time data, and optimizing application performance for real-time updates. We also learned that Google API is a pain to work with especially when you are initially trying to import the API. In addition, we also learned the importance of user feedback in shaping a user-centered design and functionality.

What's next for Danger Tracker

Looking ahead, we aim to expand the application's capabilities by including more types of hazards and support additional regions globally. We're exploring the integration of machine learning algorithms to predict potential dangers more accurately. Additionally, developing a community-driven feature where users can report and share updates on emerging hazards is on our roadmap, fostering a collaborative environment for public safety.

The future of our product is to address the vulnerabilties and means of abusing our software. For one, it is far too easy for users to miss-identify something innocuous as a hazard, or even a crime. Our software does open itself up for misuse by bad-actors, and can even be used to attack minorities in the city. We should focus on these issues first and foremost.