Abstract
Mobile ubiquitous computing has not only enriched human comfort but also has a deep impact on changing standards of human daily life. Modern inventions can be even more automated by using the Internet of Things (IoT) and Artificial Intelligence (AI). Mobile devices, body area networks, and embedded computing systems allow healthcare providers to continuously assess and monitor their patients but also bring privacy concerns. This paper proposes a smartphone-based end-to-end novel framework named PP-SPA for privacy-preserved Human Activity Recognition (HAR) and real-time activity functioning support using the smartphone-based virtual personal assistant. PP-SPA helps to improve the routine life functioning of the Cognitive Impaired individuals. PP-SPA uses a highly accurate machine learning model that takes input from smartphone sensors (i.e., accelerometer, gyroscope, magnetometer, and GPS) for accurate HAR and uses a digital diary to recommend real-time support for improvement in individual's health. PP-SPA yields a proficient accuracy of 90% with the Hoeffding Tree and Logistic Regression algorithm which endeavors reasonable models in terms of uncertainty.