Overall Architecture
Patient Data Privacy Architecture

iCare Central - AI-Powered Smart Wheelchair & Health Management System

Inspiration

Caring for elderly individuals and those with mobility challenges can be overwhelming for caregivers. We wanted to create a system that not only enhances mobility but also provides real-time health monitoring, ensuring both independence for users and peace of mind for caregivers. The idea was inspired by the need for smarter assistive technology that integrates AI-driven navigation with holistic patient care.

What it does

iCare Central is an AI-powered system that combines smart wheelchair navigation with real-time health monitoring. Using eye-tracking technology, users can control their wheelchairs effortlessly, while integrated sensors track vital signs like heart rate variability. The caregiver dashboard provides real-time alerts, health trends, and emergency notifications, ensuring proactive care and swift intervention when needed.

How we built it

We designed iCare Central with a modular architecture, ensuring scalability and flexibility. The system consists of:

AI-powered eye-tracking navigation for wheelchair control
Camera-based health monitoring for real-time vital tracking
IMU-based movement detection for stability and fall prevention
A secure database for storing patient health and mobility data
A responsive web app that enables caregivers to monitor and assist patients remotely

Development involved training AI models for eye tracking, integrating real-time data processing for health monitoring, and optimizing a seamless user interface for both patients and caregivers.

Tech Stack

Frontend: React.js, Material-UI, Redux, WebSocket
Backend: Node.js, Express.js, MongoDB, Python
AI & ML: TensorFlow.js, OpenCV, Deep Learning models for eye tracking
Infrastructure: Docker, AWS, Prometheus, Grafana for monitoring

Challenges we ran into

Eye-tracking precision: Ensuring accuracy across different lighting conditions and user variability was a challenge. We fine-tuned the model using diverse datasets.
Real-time health monitoring: Processing camera-based heart rate variability (HRV) required optimizing algorithms to reduce lag while maintaining accuracy.
Data security & compliance: Handling sensitive health data required implementing strong encryption, authentication, and compliance with HIPAA and GDPR standards.
Hardware integration: Synchronizing multiple sensors and ensuring seamless communication between software and hardware components took rigorous testing and debugging.

Accomplishments that we're proud of

Successfully integrating AI-driven eye tracking with wheelchair navigation
Developing real-time health monitoring with minimal latency
Building a caregiver dashboard with actionable insights and alerts
Implementing security measures to ensure safe and private data handling
Creating a scalable, modular system that can be expanded with additional features

What we learned

The importance of user-centric design for accessibility and ease of use
How to optimize AI models for real-time applications with constrained hardware
Effective data processing techniques for continuous health monitoring
Best practices for security and compliance in healthcare applications
How to seamlessly integrate software and hardware for a smooth user experience

What's next for iCare

We plan to expand iCare Central with:

Voice-controlled navigation for hands-free wheelchair operation
Predictive health analytics using AI to detect early signs of medical conditions
IoT integration for smart home connectivity, allowing users to control their environment
Expanded caregiver tools for remote patient management and automated health reports
More accessibility features such as gesture-based controls and multilingual support

iCare Central is just the beginning of transforming elderly and patient care through AI and smart technology!