A Performance Improvement in Home Automation Through Uncontaminated Energy Interfaced with Multi Dimensional Machine Learning Approach

The Management of devices often used in current homes is designed in terms of automation. This means that the energy and power required for the operation of that particular type of device will be calculated and supplied accordingly. It does not take place through human activities in any way. These operations, which take place entirely automatically, take up a lot of energy in some places. Thus there is not enough energy available to operate other devices. A machine learning method is proposed here to deal with this effectively. It records the nature of the machine and the energy and power required for it in advance in the database. It will provide the energy it needs based on those records. Then check the machine module again. If there is too much energy it will do it to another machine and so on. This reduces energy consumption by up to 70% and reduces power consumption by 62%. Furthermore, the results of the study clearly show that the energy utilization is 97% due to the use of this method.