| Abstract |
Energy consumption in smart cities relates to every energy consumed to carry out an activity, produce something, or exist in a structure. The most common measurement of energy efficiency is energy consumption per square meter in city residential areas. The states' problematic energy consumption characteristics in smart cities may include climatic change, rainfall issues, water scarcity, and electricity generation. Thus, based on the states of households, an expanded proposed system of statistic determination impact conversion by positive, accurate technology (STIRPAT) model has been developed. STIRPAT model is collaborative research that aims to learn about the dynamic connections between human systems and the surrounding environment. There are two methods of the STIRPAT model to satisfy the characteristic of the proposed approach. The energetic counseling framework is an emerging technique that overcomes climatic change, electricity generation, and rainfall issues by sensing it in the environment. An algorithmic approach of the standard genetic method offers to conclude the problems into a cloud block mechanism for visualizing the states. Thus, the integrated technique of these two methods shows the factual implementation to overcome the statistical problems. Further research shows that, since the significant effect had been taken into account, the energy consumption per square meter in metropolitan residential buildings peak occurred eleven years later than without considering the dilution effect. The performance ratio of the STIRPAT model is estimated to be 98.3% by comparing with overall researches. |
