Capstone Project - Armadillo Armadillo: AI-Powered Patient Identity and Security Management System
Welcome to the Armadillo project! This repository contains the source code, documentation, and resources for a patient identity and security management system, developed as part of the University of Wollongong’s CSIT321 project in collaboration with Sample Assist Pty Ltd.
Project Overview
The Armadillo project aims to solve two critical challenges in healthcare:
1. Patient Identity Verification: Utilizing Optical Character Recognition (OCR) to automate and improve patient identity verification.
2. Data Security and Anomaly Detection: Enhancing data security using Machine Learning (ML) models to detect threats and anomalies in patient records.
This project integrates advanced AI tools to automate administrative processes, reduce human error, improve data integrity, and enhance operational efficiency in healthcare environments.
Features
• OCR-Driven Identity Verification
• Automatically scans and processes identity documents (e.g., passports, driving licenses).
• Populates medical forms to streamline the patient onboarding process.
• Reduces administrative load on healthcare staff and minimizes data errors.
• Anomaly and Threat Detection
• Implements user behavior analysis (UBA) and threat detection to safeguard patient data.
• Provides real-time monitoring and alerting for unauthorized access or anomalies.
Project Benefits
• Saves time and reduces administrative costs.
• Enhances data integrity and improves patient safety.
• Provides a better patient experience by automating identity verification.
• Mitigates security risks with real-time threat detection.
Stakeholders
• Primary Users: Doctors, nurses, hospitals, clinics, laboratories, and patients.
• Client and Partner: Sample Assist Pty Ltd.
• Development Team: University of Wollongong CSIT321 project students.