Renewable Wind Energy using IoT-Based Smart Appliances
| International Journal of Computer Science and Engineering |
| © 2022 by SSRG - IJCSE Journal |
| Volume 9 Issue 11 |
| Year of Publication : 2022 |
| Authors : R. Surendiran, M.Thangamani |
10.14445/23488387/IJCSE-V9I11P101
How to Cite?
R. Surendiran, M.Thangamani, "Renewable Wind Energy using IoT-Based Smart Appliances," SSRG International Journal of Computer Science and Engineering , vol. 9, no. 11, pp. 1-8, 2022. Crossref, https://doi.org/10.14445/23488387/IJCSE-V9I11P101
Abstract:
Electricity is one of the key factors in human life to survive on the earth. Major of our work requires electricity so it is important to power saving. It is difficult to get power from the rain in the solar panel. So, we proposed an energy-efficient IoT-based smart appliance, renewable wind energy. The term "distributed energy resource system" refers to the fusion of one or more energy sources in a power method. In this research, smart appliances are used to save energy while considering the aforementioned concerns. A detailed comparative results analysis of some Deep Learning (DL) based Smart Appliances in terms of precision, specificity, accuracy and recall. The Convolution Neural Network (CNN) based Smart Appliances method outperformed. The suggested framework is compared with existing methods such as HGPDO, CNN, and ANN in terms of Accuracy, precision, Recall, and Specificity. According to experimental findings, the proposed technique extends smart appliances by 50%, 9.756%, and 26.829%, compared with HGPDO, CNN, and ANN Methods.
Keywords:
Convolution Neural Network, Deep Learning.
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