Abstract:

Health consciousness is the main emphasis, and testability increases with age. Taking care of the elderly is therefore a great responsibility. Technology saves lives in situations like these by providing life support. "Falls" are a significant cause of poor health and ageing. This study suggests a fall detection system based on machine learning. The technology detects falls and alerts senior student parents or carers in the case of an emergency by classifying different behaviours into falling and non-falling categories. The SisFall dataset, which includes a variety of activities from many individuals, is used to compare the attributes. SVM and decision tree machine learning algorithms are used to detect droplets based on calculated properties. The decision tree method is used by the system to get an accuracy of up to 96%.

Description:

.