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.
Keywords
Deep learning, Intelligent-IOT, Accuracy, DNN, WSN.
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