Internet of Things and wearable device-basedtracking of an elderly person's physical activity

The potential for real-time activity tracking (R- TAT) to shed light on the health and habits of the elderly is a major reason why it should be widely adopted. This strategy allows for the unobtrusive collecting and analysis of data connected to a person's day-to-day physical activities by deploying wearable devices equipped with sensors and leveraging the connectivity of IoT. These details can be crucial in the early diagnosis of health problems, allowing for prompt interventions and individualized healthcare plans. Ethical constraints, data privacy, and the requirement for userfriendly gadgets offer considerable challenges to mainstream adoption. To facilitate real-time monitoring while giving top priority to data integrity and confidentiality, a new algorithm called the IoT-Enabled Data Transmission Privacy Recognition Algorithm (IoT-DTPRA) has been suggested in the present research. Provides fine-grained control over data sharing options and uses strong measures like encryption and anonymization to preserve the privacy of senior citizens' personal information. Caretakers, healthcare professionals, and family members all benefit from the actionable information provided by IoT-DTPRA since it provides a comprehensive and privacy-conscious way to monitoring the physical activity of the elderly. The suggested methodology is verified using simulation analysis, which use actual situations and synthetic datasets to assess the IoT-DTPRA system's performance in a range of environments. The methodology's reliability and robustness across a wide range of physical activities and environmental circumstances have been verified by this thorough validation.