Long waiting rooms are the biggest complaint in small clinics: patients come early, sit for an hour and still do not know when their turn will come. ClinicQ is a doctor appointment Android project that fixes this. Patients book a time slot from the app and get a token like A-18. A live token board shows who is with the doctor now, how many patients are ahead and an AI estimate of when their turn will come, so they can leave home at the right time. After the visit the doctor writes an e-prescription in the app and the patient gets it as a PDF with medicine reminders.
How it works
- The patient types symptoms and the AI symptom checker suggests the right specialist (General Physician, Paediatrician, Dermatologist and more), with an emergency rule for red-flag symptoms
- The patient picks a doctor, date and free slot and gets a queue token
- The live token screen refreshes every 10 seconds and a regression model trained on the doctor's past visits predicts the waiting time
- The doctor calls the next token, marks done or skips from the queue screen
- The doctor writes the prescription from a medicine list; the app warns about allergies (for example sulfa drugs) and medicine interactions
- The patient downloads the PDF prescription, reads a simple explanation in English, Hindi or Marathi and gets dose reminders
- The admin manages doctors, timings, leaves and medicines and sees the clinic's daily load
Users
- Patient: symptom check, booking for self and family, live token, prescriptions, reminders, health records, reviews
- Doctor: today's queue, patient history with BP chart, e-prescription, schedule and leave, stats and reviews
- Admin (web panel): dashboard, doctors and specialties, timings, leave approval, medicines, appointments, printable prescriptions, reports, notices, settings
Highlights
- 3 roles, 24 Android screens, 13 admin pages, 38 PHP APIs, 15 MySQL tables
- 3 AI/ML features: AI symptom checker (Gemini + offline matcher), wait-time prediction with multiple linear regression, prescription explainer in 3 languages
- Allergy and drug-interaction check on both app and server
- PDF prescription, medicine reminders with streak, hourly load heat map and charts
- Full validations in app and server (email, 10-digit mobile, password, dates, file type and size), hashed passwords, prepared SQL
- Sample data for 60 days with demo logins, so every chart and queue works on the first run
What you get
- Complete source code: Android app (Java) and web panel with APIs
- MySQL database file with sample data
- Project report (Word, 56 pages, all UML / DFD / ER diagrams)
- Project abstract, project explanation with viva questions, setup guide
- One-to-one online installation and code explanation session
Who can use this project
Final year BE / B.Tech, MCA, BCA and Diploma students of Computer Engineering and IT who need an Android project with source code, documentation and report on healthcare, appointment booking or AI.
Frequently asked questions
Will the app work without a Gemini API key? Yes. The symptom checker and prescription explainer have offline versions, so the demo works without internet AI.
How is the waiting time predicted? The app trains a multiple linear regression model on the doctor's last 60 days of visits (hour of day, follow-up or new visit, Monday rush) and adds the predicted time of every patient ahead.
Can a patient book for parents or children? Yes. Family members are added once and can be selected while booking; their prescriptions and records stay separate.
Can I show the live queue in a viva? Yes. Log in as the doctor on one device and as the patient on another, press "Call next" and the patient's token board updates within 10 seconds.
