Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments

Abstract

The outer surface of the building is the same size as its premises, with greater heat loss. Therefore, when building, renovating, or expanding apartment, if possible, avoid all kinds of spaces, ledges, and lodges in the walls. It makes sense to build unheated exterior buildings on the north side of the apartment. The storage rooms for garden tools and bicycles, technical buildings protect the warm part of the house from wind and cold. In the most common design of a private apartment, the energy consumption for heating is 110-130 kW per 1 m2 per year. In this paper, an energy distribution model was proposed to estimate the photo energy with the help of deep learning model. A small apartment not only uses less energy but also requires lower construction costs. An energy-efficient apartment is a building with a low-energy consumption and comfortable microclimate. Energy savings in such homes can be up to 90%. Annual heat demand can be less than 15 kWh per square meter of energy-efficient home.