Fostering Analysis of Livelihood Pre and Post Covid-19 using ML Techniques

Abstract

The energy sector is one of the major disrupted industries during the time of the lockdowns in all countries. This is causing an irregularity in supply and demand creating various challenges to the sector. The paper provides a comprehensive view on the factors affecting the power usage by the households and the change in trends of consumption of electricity. The paper also included the mental health of the people before and after the COVID lockdown. Two models were created, linear regression for power consumption and logistical regression for mental health. They were verified using various techniques. The purpose of these models is to help researchers and enthusiasts get a better idea about the relationship between various factors which are affecting the power consumption and mental health during the lockdown. They can also be used to predict the outcome if incase any similar event occurs in future.