Artificial Intelligence-Based Smart Health Monitoring Framework for Elderly Individuals
1st Margana Saidurgarao 2nd Kandukuri Tharunasri 3rd Raja Moyilla
Dept. Computer Application, Aditya University, Surampalem, India raomarganasaidurga@gmail.com
tharunasri9@gmail.com rajmoyilla@gmail.com
4th Baladari Poojitha 5th Chodisetty Bhavani S R Samhitha
Dept. Computer Application, Aditya University, Surampalem, India
poojithabaladari29@gmail.com chodisettyradhasamhitha@gmail.com
Abstract—The swift increase in the population of the elderly has now been one of the greatest challenges confronting the healthcare systems all over the world. Older persons are more prone to chronic illnesses that include cardiovascular disorders, diabetes, respiratory illnesses, and neurological disabilities. The constant observation of major health parameters is required to identify possible medical complications or provide adequate medical intervention in time. Nevertheless, the conventional system of healthcare heavily depends on the regular visits to the hospital or the use of the manual monitorization that can postpone the recognition of the critical health issues. As Internet of Things (IoT) technologies and Artificial Intelligence (AI) have developed, smart healthcare monitoring systems proved to be helpful tools in enhancing the process of managing the elderly.
The present study offers an Artificial Intelligence-oriented smart health monitoring system that will be specific to the elderly. The target system combines the wearable and the IoT-based communication infrastructure, machine-learning algorithms, and cloud-based healthcare services to offer a constant check of the physiological parameters. The system is used to gather real-time health information that includes heart rate, body temperature, the saturation of oxygen in the blood, blood pressure, and physical activity trends that are obtained with the help of wearable devices. Wireless communication networks transfer these data to an AI based processing system where machine learning programs process these data and detect abnormal health conditions.
Predictive analytics have also been included to the proposed framework to identify possible health risks and automatically create alerts to caregivers and the medical community in case of abnormal conditions. The experimental findings also suggest that the AI-based monitoring model is much more accurate in prediction and has a shorter response time than the conventional monitoring methods. The proposed system offers an intelligent and scalable healthcare system that would be able to enhance the quality of life of older people because it would allow proactive care management and early disease diagnosis.
Keywords: Artificial Intelligence, Smart Healthcare, Elderly Health Monitoring, Internet of Things, Machine Learning, Remote Healthcare Systems, Intelligent Health Analytics.
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