As the world’s population is aging continuously, the need for healthcare support services, particularly those related to fall-related injuries, is poised to surge. Effective fall detection technology can alleviate this strain on healthcare resources and reduce the burden on caregivers and family members. The increasing prevalence of health issues in the aged has highlighted the need for innovative healthcare solutions prioritizing safety, independence, and proactive health management. The risk of falling while walking is a significant concern among the many challenges elders face with certain medical conditions. Falling can lead to severe injuries and complications, making timely detection and response needed to safeguard individuals’ health. The significance of this problem is multifaceted and profound. Rapid detection and response to falling can mitigate these consequences, thereby enhancing the safety and health of individuals. In this article, we proposed wristband-integrated deep-learning techniques for wearable sensors. The use of mobile applications exemplifies the potential of technology to revolutionize healthcare. It underscores how AI-driven solutions can empower individuals to lead independent lives while providing comprehensive support for their health needs. The proposed device further seamlessly combines fall detection with medication reminders. This approach promotes proactive healthcare management. Adherence to medication regimens is critical for individuals with chronic conditions, and technology can simplify and enhance this aspect of self-care.