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Mediquick - AI Based Emergency Hospital Bed Booking System

“Emergency Care, Instantly there”

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Inspiration

Every second matters in a medical emergency. But patients are often stuck figuring out where to go, what's available, and how to get there. This prototype removes that friction using AI + smart hospital matching — prioritizing lives over logistics." We wanted to fix that.

So I built MediQuick — an AI-powered emergency triage and bed booking system that shows real-time bed availability and helps people get admitted faster and smarter for better health and well-being of users.

What It Does

  1. User enters symptoms into a form.
  2. AI logic checks if it's an emergency based on the symptoms.
  3. If urgent, the system automatically books a bed at the nearest hospital with availability.
  4. Displays confirmation so the user can directly head to the hospital.
  5. All done without requiring upfront payment — because saving lives shouldn’t depend on your wallet.

🛠️ How I Built It

  • Frontend: HTML, CSS, JavaScript — designed to be minimal and fast.
  • Backend: Flask (Python) — with routes for symptom checking, hospital search, and booking logic.
  • Database: MySQL — stores hospitals, bed availability, and booking data.
  • AI Logic: Logistic Regression for finding the emergency, Random Forest for finding the category of emergency
  • Booking Logic: Automatically assigns the nearest available hospital bed based on location and need.

Note: IoT integration and routing APIs are planned for future versions but not included in this prototype.

🧗‍♀️ Challenges I Ran Into

  • Handling realistic bed booking scenarios while keeping it simple.
  • Designing a working demo without real hospital APIs.
  • Balancing automation (auto-booking) vs user control (manual hospital choice).
  • Making emergency detection work reasonably well with basic symptom input.

Accomplishments That I am Proud Of

  • Built a full working prototype from front to back 💪
  • Simulated a real-world healthcare workflow with dummy data
  • Made emergency care instant and accessible for everyone
  • Got super clear on how real-world healthcare + tech can come together for good

What I Learned

  • How to structure a full-stack AI-powered solution in healthcare.
  • The complexity of triage and how tricky real-time bed tracking can be.
  • That even a basic AI system can help automate life-saving decisions.
  • How to stay focused and build what matters even with limited time.

What's Next for MediQuick

  • Add IoT simulation using FSR sensors to track real-time bed occupancy.
  • Integrate location APIs like OpenStreetMap or Google Maps for better hospital routing.
  • Expand hospital database + add filtering for specialties/doctors.
  • Train a smarter ML model for emergency detection (beyond keyword logic).
  • Improve UI/UX for smoother mobile use.
  • Deploy a real pilot in small clinics for feedback.

While MediQuick aims to revolutionize emergency care by instantly detecting emergencies and auto-booking hospital beds, I recognize that in real-world healthcare, things like hospital confirmation, insurance verification, and payment processes can complicate instant admissions. my vision is to build toward a future where life-saving care is prioritized over paperwork — but for now, I’ve simulated this streamlined experience to show what’s possible when technology puts patients first.

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