Elderly Care AI Companion

An AI-powered companion that assists elderly individuals with daily tasks, provides emotional support, and ensures their safety through reminders and health monitoring.

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Inspiration

This report outlines the development of an AI-driven companion designed to enhance elderly care by seamlessly integrating health monitoring with modern communication methods. The system employs wearable technology to track vital signs such as pulse and blood pressure, and utilizes Twilio's API to send WhatsApp notifications to registered caregivers when readings fall outside normal ranges. The backend is powered by Node.js, facilitating efficient data processing and communication management.

What it does

The global aging population presents increasing challenges in healthcare, particularly in providing continuous and responsive care to seniors. Integrating artificial intelligence (AI) and communication technologies offers promising solutions to enhance the quality of life for elderly individuals. This project focuses on developing an AI companion that monitors health metrics in real-time and ensures timely communication with caregiver

How we built it

  • Node.js Backend The backend leverages Node.js for its scalability and efficiency in handling real-time data. Express.js is used to set up the server and define API routes. A SQLite database is employed for data storage, offering a lightweight and efficient solution.
  • Twilio Integration Twilio's API is utilized to send WhatsApp messages. The integration involves setting up a WhatsApp Business Account and connecting it with Twilio to enable message sending and receiving.

Challenges we ran into

The project currently lacks a frontend interface, which limits user interaction and system accessibility. Developing a user-friendly frontend is essential for caregivers to monitor health data and manage alerts effectively. Additionally, incorporating AI capabilities can enhance data analysis, enabling predictive analytics for proactive care. Exploring AI-driven features, such as anomaly detection in health patterns, could further improve the system's effectiveness.

Accomplishments that we're proud of

Developed using Node.js, the backend server handles data reception, storage, and analysis. It processes the incoming health data and determines when to trigger alerts based on predefined thresholds. Twilio's WhatsApp Business API is integrated to facilitate direct communication between the system and caregivers. When health metrics deviate from the norm, the system sends a WhatsApp message to the registered caregiver, prompting immediate attention.

What we learned

Building the backend using Node.js showed the power of non-blocking, event-driven architecture in handling concurrent requests.

What's next for Elderly Care AI Companion

The project currently lacks a frontend interface, which limits user interaction and system accessibility. Developing a user-friendly frontend is essential for caregivers to monitor health data and manage alerts effectively. Additionally, incorporating AI capabilities can enhance data analysis, enabling predictive analytics for proactive care. Exploring AI-driven features, such as anomaly detection in health patterns, could further improve the system's effectiveness.

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