Published Paper Details:

The rapid advancements in artificial intelligence (AI) and embedded systems have paved the way for innovative healthcare solutions, especially for chronic disease management. This paper presents the design and implementation of Smart Nurse, an AI-powered robotic healthcare assistant for cancer patients. The system integrates real-time patient monitoring, emergency alert mechanisms, and medication dispensing functionalities using Raspberry Pi. Key features include a fall detection system based on YOLO and sensor data fusion, an emotion detection model combining facial expressions (ResNet-50), voice tone (MFCCs), and sentiment analysis (BERT), and an AI-driven chatbot utilizing GPT-based natural language understanding with OpenAI Whisper for speech recognition. The robot navigates autonomously using SLAM-based AI navigation with ESP32CAM and ultrasonic sensors. It communicates via a hybrid MQTT and API-based system to synchronize with a Django backend and a locally hosted database. Emergency situations trigger a loud SOS alarm and Twilio SMS alerts to caretakers. The hardware framework includes a battery-powered structure with servo-controlled gravity-based medication dispensing. The system is designed to function without cloud dependency, ensuring affordability and privacy. This paper details the system architecture, hardware-software co-design, and the implementation methodologies for AI models, real-time communication, and embedded robotics. The experimental results indicate that the system enhances patient safety, ensures timely medication, and provides emotional support, making it a promising solution for remote healthcare assistance.