| Yazarlar |
Mohammed Hasan Aldulaimi
Al-Mustaqbal University, Iraq |
|
Ibrahim Najem
Al-Turath University, Iraq |
|
Tabarak Ali Abdulhussein
Imam Ja'afar Al-Sadiq University, Iraq |
|
M. H. Ali
National University of Science and Technology, Iraq |
|
Asaad Shakir Hameed
Mazaya University College, Iraq |
|
M. Altaee
Al-Farahidi University, Iraq |
Hatıra GÜNERHAN
Kafkas Üniversitesi, Türkiye |
| Özet |
| The DTA-LI system's fusion data method is crucial in the monitoring of appliance loads for the purposes of improving energy efficiency and management. Common home electrical devices are identified and classified from smart meter data through the analysis of voltage and current variations, allowing for the measurement of energy usage in residential buildings. A load identification system based on a decision tree algorithm may infer information about the residents of a building based on their energy usage habits. Better power savings rates, load shedding management, and overall electrical system performance are the results of the clusters' ability to capture families' purchasing patterns and geo-Demographic segmentation. The DTA-LI system's fusion data method presents a promising avenue for improving residential buildings' energy performance and lowering their carbon footprint, especially in light of the widespread use of smart meters in recent years. |
| Anahtar Kelimeler |
| Appliance load monitoring | Data Fusion Techniques | decision tree algorithm | household | smart meter |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | SCOPUS dergilerinde yayımlanan tam makale |
| Dergi Adı | Journal of Intelligent Systems and Internet of Things |
| Dergi ISSN | 2769-786X |
| Makale Dili | İngilizce |
| Basım Tarihi | 01-2023 |
| Cilt No | 9 |
| Sayı | 1 |
| Sayfalar | 24 / 33 |
| Doi Numarası | 10.54216/JISIoT.090102 |
| Atıf Sayıları | |
| SCOPUS | 5 |
