Detection of Human Activity by Widget

Human Activity recognition exhibits its presence in diverse research areas like medical organization, Survey system, security surveillance as well as human computer interaction. This work demonstrates a robust approach of classifying six basic human centered behaviors (Walking, Walking Upstairs, Walking Downstairs, Sitting, Standing, and Lying implementing Logistic Regression, Logistic Regression CV and Random Forest algorithm. Computing is an up-and-coming research to comprehend individual actions and try to assimilate their social context. A precise demanding and agreeable application of sensing human body motion by smart phones to collect context information. Here, activity recognition database is considered publicly available as repository.