MEasily

Instant AI measles triage that turns a selfie & voice note into a risk score, then lights up a community-wide exposure map and steers users along the safest, low-risk route to their next errand.​

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Inspiration

With the recent recurrence of measles outbreaks across the United States, we felt a familiar sense of urgency, reminiscent of previous widespread diseases. This inspired us to develop a proactive solution to minimize the spread of this highly contagious illness.

What it does

MEasily is a web application designed to provide rapid, AI-driven health assessments and community safety tools. Users submit their symptoms through audio, text, or images, and our AI evaluates their measles risk. If a high risk is detected, their general location is anonymously added to a community heatmap to inform others about potential exposure zones. Additionally, if a user plans to visit a high-risk area, MEasily suggests safer alternatives and provides routes that avoid infected zones.

How we built it

We divided the development into four core parts:

  • Diagnosis Backend: Built with Python (Flask), integrating Groq’s multimodal AI API for symptom analysis.
  • Risk Assessment: Utilized Gemini’s AI to analyze risk levels based on reported symptoms.
  • Mapping and Routing Backend: Leveraged Fetch.AI's asi1-mini and Google Maps agent to suggest safer travel routes.
  • Frontend Interface: Developed using React with Google Maps API integration for interactive visualizations.

Throughout, we emphasized constant communication to ensure smooth integration.

Challenges we ran into

  • Ensuring accurate AI interpretation of multimodal symptom inputs.
  • Balancing precise, real-time mapping data while preserving user privacy.
  • Seamlessly integrating diverse technologies (Flask, React, Groq, Fetch.AI, Gemini) into a cohesive user experience.

Accomplishments that we're proud of

  • Successfully creating an integrated solution that combines health diagnostics, real-time mapping, and intelligent routing recommendations.
  • Implementing our own mathematical models to optimize route suggestions, significantly enhancing user safety.
  • Developing a practical, user-friendly tool that actively contributes to community health awareness.

What we learned

  • Clear, timely communication is critical for integrating multiple complex technologies.
  • Deepened our understanding of privacy considerations in health-related applications.
  • Improved our skills in AI integration and real-time data handling.

What's next for MEasily

  • Expand to other contagious diseases for broader health monitoring.
  • Partner with local health agencies to enhance community outreach and public health responsiveness.
  • Incorporate user feedback loops for continuous improvement and greater user engagement.

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