Inspiration

In 5th grade, the members of our team made a project about the future of technology, and that was AI and machine learning. Ever since then, we have been fascinated by the idea of using AI to solve real-world issues. We wanted to create a tool for victims of domestic abuse that does more than just list resources, but a tool that is responsive, smart, and supportive. A member of our team has had close friends that have been through domestic abuse in relationships. With this experience, we were inspired to create a viable product that victims can actually use. We are motivated by working towards the safety of domestic violence victims

What it does

We use AI to evaluate a severity score based on the log incidents the user provides. Based on that data provided we give them the recommended steps to take to ensure their safety, as well as provide with resources on where to get immediate help.

How we built it

Tech Stack: Frontend

  • React Native for component-based architecture
  • Expo for development and navigation
  • JavaScript (mostly function components + useState) Backend
  • Node.js, express, express.js, mongodb, rest api, toxicBert

Main Screens We Coded:

  1. Home Screen – a dashboard with buttons for each main feature
  2. Document Incidents Page – lets you write down what happened, when, and how it made you feel.
  3. Timeline Page – uses a FlatList to show all the incidents with dates, descriptions, and emotions in styled cards.
  4. Next Steps Page – uses the severity of the situation to show recommended steps.
  5. Resources Page – shows support hotlines, organizations, etc., split into categories like legal, mental health, and crisis.

Challenges we ran into

  • Finding NLP AI to suit our needs
  • Designing a welcoming and user friendly UI
  • Time managment
  • Sleep

Accomplishments that we're proud of

  • Comforting and aesthetically pleasing UI
  • Interactive and engaging features
  • Applicable for real-world scenarios
  • AI implementation

What we learned

  • UX/UI design features
  • Managing Data
  • Conditional Rendering
  • Database implementation
  • Use of AI for NLP

What's next for Safespace

  • User accounts & privacy
  • Location-based resources
  • Even more accurate severity evaluation

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