Demo Projects - Innov8Code

MedCare - Professional Healthcare Management System

Comprehensive healthcare management platform with patient, doctor, and hospital portals featuring appointment scheduling, medical records, AI-driven health insights, and administrative tools.

Duration: 1 week

Technologies:

Python Flask MySQL Bootstrap JavaScript Chart.js FontAwesome

Key Features:

User Registration and Authentication
Role-based Access Control (Patient/Doctor/Hospital)
Patient Portal with Appointment Booking and Health Timeline
Doctor Portal with Appointment Management and Patient Records
Hospital Portal with Staff and Resource Management
Secure Document Upload and Management
Interactive Charts and Data Visualization
Responsive and Accessible UI Design
HIPAA-compliant Security Features

SignLingo - Real-time Sign Language Detection

AI-powered desktop application for real-time sign language detection and recognition using webcam video input. The system leverages MediaPipe for hand landmark tracking and a pre-trained machine learning model for gesture classification.

Duration: 3 days

Technologies:

Python OpenCV MediaPipe Tkinter NumPy Pillow Scikit-learn

Key Features:

Real-time gesture detection via webcam
AI model for sign language recognition
Modern Tkinter-based user interface
Vocabulary panel with supported gestures
Start/Stop detection controls
Confidence and system status indicators
Bounding boxes and hand landmarks overlay

Plant Leaf Disease Detection Using Mask R-CNN

A deep learning-based system for detecting and classifying plant leaf diseases using Mask R-CNN and U-Net architectures. Provides high-accuracy real-time segmentation and classification to support agricultural disease management.

Duration: 10 days

Technologies:

Python Flask Mask R-CNN U-Net NumPy OpenCV HTML CSS JavaScript

Key Features:

Real-time plant leaf disease detection
Deep learning models using Mask R-CNN and U-Net
High-accuracy segmentation and classification
Web deployment using Flask
Responsive HTML/CSS/JavaScript front end
User-friendly interface for uploading and analyzing images
Supports multiple plant species and disease types
Scalable architecture for agricultural use

Intelligent Multi-Disease Diagnosis System

A health prediction web application built using the Flask framework, featuring trained machine learning models for diagnosing diabetes, heart disease, and Parkinson's disease. Incorporates SVC and Logistic Regression algorithms for real-time classification.

Duration: 2 days

Technologies:

Python Flask Scikit-learn Pandas NumPy HTML CSS Bootstrap

Key Features:

Real-time health predictions for multiple diseases
Machine learning models for diabetes, heart disease, and Parkinson's
Support for SVC and Logistic Regression classifiers
User-friendly interface with organized input forms
Display of prediction results with basic health advice
Responsive design for desktop and mobile
Data preprocessing for accurate predictions
Early diagnosis support for timely user action

Our Demo Projects Portfolio

MedCare - Professional Healthcare Management System

Key Features:

SignLingo - Real-time Sign Language Detection

Key Features:

Plant Leaf Disease Detection Using Mask R-CNN

Key Features:

Intelligent Multi-Disease Diagnosis System

Key Features:

Project Demo