Automation of Smart Home for the Wellbeing of Elders Using Empirical Big Data Analysis

Globally, the research community has been extremely concerned about the recent sharp rise in the proportion of elderly individuals. Studies are being done actively to make use of the advantages of ICT that allow them to live autonomously and encourage overall wellness. Smart homes are frequently used to help this population. Nevertheless, there is a dearth of pertinent empirical studies that attempt to quantify and analyze these individuals' intentions to use that kind of service. In this research, we suggest an autonomous smart home application that is energy-efficient and combines big data and cloud computation to supervise seniors. A smart multimedia-based supervisor that enables an elderly individual to observe various energy-efficient mechanisms, regulate smart home devices via gestures, receive alerts concerning device status updates, and distribute multimedia information with a group of interest is developed. An autonomous switch on/off management device employing speech or gestures has been created to preserve energy. Speech-based keywords are recognized and employed as control signals. The promising prospect of using this architecture on a massive scale is demonstrated by empirical outcomes.