SafetySphere

Inspiration

Women’s safety continues to be a serious concern, especially during late hours or in unfamiliar locations. Most safety apps respond after an incident occurs. We wanted to create something that could help prevent unsafe situations before they happen. That idea inspired us to build SafetySphere — a platform that uses AI to predict risk and empower safer decision-making.

What it does

SafetySphere is an AI-powered web platform that helps users evaluate the safety of a location in real time. It analyzes factors like time, crowd density, lighting conditions, and location type to generate a risk score. The platform also provides safe route suggestions, visual heatmaps of unsafe zones, and an emergency SOS feature for instant alerts.

How we built it

We developed SafetySphere using a full-stack architecture. The frontend was built with React.js to create a responsive and user-friendly interface. The backend was implemented using Node.js and Express for API handling and authentication. MongoDB was used for storing user data and alerts. A Python-based AI module calculates risk scores using a weighted prediction model. All components were integrated to work seamlessly together.

Challenges we ran into

One major challenge was integrating the Python AI module with the Node.js backend. Ensuring smooth communication between services required careful API design. We also faced limitations due to the lack of real-world safety datasets, so we had to simulate realistic risk scenarios. Managing time efficiently during development was another important challenge.

Accomplishments that we're proud of

We are proud of building a complete and functional full-stack application within the hackathon timeframe. Successfully integrating AI into a real-world safety use case was a significant achievement for our team. Most importantly, we created a project that addresses a meaningful societal issue.

What we learned

Through this project, we learned how to integrate AI models into web applications, design RESTful APIs, and manage team collaboration effectively. We also understood the importance of ethical considerations when building technology related to safety and human well-being.

What's next for SafetySphere

In the future, we plan to integrate real-time public safety data to improve prediction accuracy. We also aim to enhance the AI model using larger datasets and advanced algorithms. Expanding SafetySphere into a mobile application and adding multilingual support are part of our long-term vision.

Built With

• ai
• ai-powered
• analysis
• backend
• charts/data
• client-side
• data
• database
• fetching
• form
• functions
• hook
• lovable
• query
• react
• recharts
• risk
• router
• routing
• tanstack
• visualization
• zod