Implement DNN technology by using wireless sensor network system based on IOT applications
Abstract
The smart Internet of Things-based system suggested in this research intends to increase network and application accuracy by controlling and monitoring the network. This is a deep learning network. The invisible layer's structure permits it to learn more. Improved quality of service supplied by each sensor node thanks to element-modified deep learning and network buffer capacity management. A customized deep learning technique can be used to train a system that can focus better on tasks. The researchers were able to implement wireless sensor calculations with 98.68 percent precision and the fastest execution time. With a sensor-based system and a short execution time, this article detects and classifies the proxy with 99.21 percent accuracy. However, we were able to accurately detect and classify intrusions and real-time proxy types in this study, which is a significant improvement over previous research.
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PDFDOI: http://dx.doi.org/10.21533/pen.v10i2.2831
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Copyright (c) 2022 Saif Saad Hameed, Haider Rasheed Abdulshaheed, Zaydon L. Ali, Hassan Muwafaq Gheni
This work is licensed under a Creative Commons Attribution 4.0 International License.
ISSN: 2303-4521
Digital Object Identifier DOI: 10.21533/pen
This work is licensed under a Creative Commons Attribution 4.0 International License