Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments
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...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Photoenergy |
| Online Access: | http://dx.doi.org/10.1155/2022/1048378 |
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| author | Komala C R S. Vimal G. Ravindra P. Hariramakrishnan Shaik Razia S. Geerthik K. Raja V. Mohanavel Nedumaran Arappali |
| author_facet | Komala C R S. Vimal G. Ravindra P. Hariramakrishnan Shaik Razia S. Geerthik K. Raja V. Mohanavel Nedumaran Arappali |
| author_sort | Komala C R |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-609dfca033e94914afb88dbd18446cfe |
| institution | Kabale University |
| issn | 1687-529X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Photoenergy |
| spelling | doaj-art-609dfca033e94914afb88dbd18446cfe2025-02-03T05:57:24ZengWileyInternational Journal of Photoenergy1687-529X2022-01-01202210.1155/2022/1048378Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart ApartmentsKomala C R0S. Vimal1G. Ravindra2P. Hariramakrishnan3Shaik Razia4S. Geerthik5K. Raja6V. Mohanavel7Nedumaran Arappali8Information Science and Engineering DepartmentDepartment of Computational IntelligenceDepartment of Electrical and Electronics EngineeringDepartment of Electrical and Electronics EngineeringDepartment of Computer Science and EngineeringDepartment of Information TechnologyDepartment of Mechanical EngineeringCentre for Materials Engineering and Regenerative MedicineSchool of Electrical and Computer EngineeringThe 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.http://dx.doi.org/10.1155/2022/1048378 |
| spellingShingle | Komala C R S. Vimal G. Ravindra P. Hariramakrishnan Shaik Razia S. Geerthik K. Raja V. Mohanavel Nedumaran Arappali Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments International Journal of Photoenergy |
| title | Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments |
| title_full | Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments |
| title_fullStr | Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments |
| title_full_unstemmed | Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments |
| title_short | Deep Learning for an Innovative Photo Energy Model to Estimate the Energy Distribution in Smart Apartments |
| title_sort | deep learning for an innovative photo energy model to estimate the energy distribution in smart apartments |
| url | http://dx.doi.org/10.1155/2022/1048378 |
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