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Android • CNN + Decision Tree • Firebase

Injury Prediction & Prevention App (Android + CNN)

A production-ready injury prediction android app built in Java/XML with Firebase Realtime Database and Google Map API. The app combines CNN image analysis for visible injuries and a Decision Tree over a quick questionnaire to estimate type and severity. It recommends first-aid steps, shows nearby hospitals, and offers video tutorials. Includes an AI chatbot for instant answers.

Important: This project is for educational and triage support only—not a medical device and not a substitute for professional care. In emergencies, call local emergency services immediately.
  • Camera/gallery input + dynamic questionnaire
  • TFLite CNN on device; instant guidance with confidence scores
  • Map to doctors/hospitals; tutorial videos tab
Delivery in 3–5 days • Pan-India support
*Demo video placeholder. Replace with your link.
Project Objective

Deliver an intuitive, privacy-aware first aid android app that helps users quickly assess common injuries and find credible next steps. The solution blends computer vision with rule-based reasoning and location services to move users from confusion to action in minutes.

How It Works
  1. Capture: User selects/takes an injury photo (cuts, bruises, burns, bleeding).
  2. Questionnaire: Short form captures pain level, duration, incident cause, age group, allergies, etc.
  3. CNN Inference: The photo is normalized and run through a TFLite CNN to predict injury class with confidence.
  4. Decision Tree: Form responses are scored to estimate severity and flag red-alerts (e.g., heavy bleeding, burns on face/hands).
  5. Guidance: The app shows first-aid steps, a link to nearby hospitals on Google Maps, and relevant video tutorials.
  6. Chatbot: An AI assistant answers follow-up questions in simple language.
Project Modules
Image Intake (CNN)

Camera/gallery → preprocessing → TFLite CNN.

  • Crop/resize/normalize
  • On-device inference
  • Confidence display
Questionnaire (Decision Tree)

Context signals → severity & triage.

  • Threshold rules
  • Red-alert flags
  • Explainable output
Guidance & Videos

First-aid steps + tutorial tab.

  • YouTube/WebView
  • Share & bookmark
  • Offline cache
Maps & Nearby Care

Find doctors/hospitals quickly.

  • Distance sorting
  • Call/WhatsApp CTA
  • Directions in Maps
Guidance is informational only. Always consult a qualified clinician. For life-threatening conditions, call emergency services immediately.
Key Features & Benefits
  • Fast triage—combine visual clues with context for better suggestions.
  • Explainable results—confidence scores and rule highlights.
  • Nearby care—maps, distance, and one-tap calling.
  • Education-first—trusted first-aid tutorials in a dedicated tab.
  • Secure & private—authentication and minimal data retention.
Android Integration Sketch (Java/XML)
// PSEUDO-CODE (illustrative only; no Firebase JSON)

// 1) Image capture + CNN (TFLite)
class CnnClassifier {
  Interpreter tflite;
  List labels;
  CnnClassifier(AssetManager am){
    // load model.tflite and labels.txt
  }
  Result predict(Bitmap bmp){
    // resize -> float32 tensor -> tflite.run() -> softmax
    // return {className, confidence}
  }
}

// 2) Questionnaire + Decision Tree
Severity assessSeverity(Answers a){
  // Example rules:
  // if a.bleeding == "heavy" or a.burnArea > threshold -> HIGH
  // else if a.pain >= 7 and swelling == true -> MEDIUM
  // else -> LOW
  // return severity + reasons
}

// 3) Combine outputs
Assessment combine(Result vision, Severity sev){
  // Merge class + severity -> recommendation + red-alerts
}

// 4) Nearby hospitals (Maps)
void showNearbyHospitals(double lat, double lng){
  // Query Places API or pass coordinates to Google Maps intent:
  // Uri uri = Uri.parse("geo:" + lat + "," + lng + "?q=hospitals");
  // startActivity(new Intent(Intent.ACTION_VIEW, uri));
}

// 5) Tutorials
void openTutorial(String ytId){
  // startActivity(Intent.ACTION_VIEW, Uri.parse("https://www.youtube.com/watch?v=" + ytId));
}

// 6) AI Chatbot (edge/callable)
ChatReply askBot(String question, UserContext ctx){
  // sanitize -> call endpoint -> return short guidance
}
              
We ship a complete Android Studio project with organized packages (camera, questionnaire, inference, maps, tutorials, chatbot), MVVM setup, runtime permissions, and secure Firebase wiring (no JSON printed here).
What You Get
ItemIncludedNotes
Android Source Code (Java/XML)Clean architecture, MVVM, comments
TFLite CNN IntegrationOn-device inference, confidence display
Decision Tree QuestionnaireExplainable severity scoring
Google Maps ModuleNearby hospitals/doctors, directions
Video Tutorials TabYouTube/WebView integration
AI Chatbot HookCommon FAQs & guidance
Demo VideoSetup & working walkthrough
Report & PPTCollege-format templates
SupportInstallation + viva Q&A (1 month)

FAQs — Injury Prediction Android App

No. It estimates likely categories and severity for educational/triage support. It is not a medical device or professional diagnosis.

Yes. Retrain/replace the TFLite model and update the label map; the UI reads labels dynamically.

Camera/Storage for photos, Location for nearby hospitals, and network for chatbot/videos. All are requested at runtime with clear consent prompts.

Questionnaire, image inference (TFLite), and cached tutorials can work offline. Maps and chatbot require connectivity.

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From setup to viva—demo videos, docs, and Q&A support.

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Add symptom chat, push alerts, or clinics’ panels.

Fair Pricing

Transparent kit + support model with coupon savings.

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