Elderly People's Abnormal Behavior Detection Using HAR and CNN Algorithms. - Paymal, Sneha Bajirao; Patil, Mahadev S. (International Journal of Intelligent Systems and Applications in Engineering, 2024)
Artificial intelligence machine learning systems are developing rapidly and very fast with the period with increasing demand and dependencies on them. New developments have been made for Artificial Intelligence and machine learning has made artificial brains for detection, identification, and decision-making abilities available for computer machines. The paper proposes the recognition of human health prediction by recognizing abnormal actions, or signs given by humans using OPENCV CNN, a tensor flow platform comparing live actions with different action datasets stored. The system detects falls of a person, sleep, heart pain, stomach pain, shoulder pain, dizziness, and different actions related to daily routine such as exercise, reading, writing, playing, makeup, etc recognize actions are sent to the Firebase cloud platform to be monitored by user or user recommended physician. Abnormal action will provide a warning message for help or raise an alarm for help. The system can detect action using surveillance cameras, or Pi camera, or a webcam.