The increasing demand for personalized and adaptive healthcare solutions for the elderly has driven the development of intelligent wearable devices that monitor vital signs and provide real-time health alerts. Our project introduces a cutting-edge smart band system leveraging Evolutionary Neural Networks, which evolve over time to optimize performance on health monitoring tasks such as analyzing heart rate, blood pressure, and physical activity. Unlike traditional health monitoring systems, which rely on static algorithms, our approach incorporates evolutionary processes—mutation, crossover, and selection—to continuously refine neural network models, ensuring they remain highly accurate and responsive to the user’s changing health conditions. Our smart band is paired with a multipurpose Android application that addresses the diverse needs of the elderly, including grocery assistance, fall detection, travel facilitation, and healthcare support. The system’s advanced image recognition technology enhances the user experience by simplifying daily tasks, such as scanning products for detailed information or securely processing transactions using QR codes. By integrating these capabilities, our smart band not only adapts to individual health patterns but also empowers elderly users with greater independence and safety. This innovative approach represents a significant advancement in long-term health management, particularly in the context of aging populations.