Abstract

With the popularization of intelligent devices and the development of internet technology, the Internet of Things technology is receiving increasing attention. However, how to effectively schedule and manage resources in the Internet of Things environment has become an increasingly important issue. In order to solve this problem, a cloud scheduling simulation system for IoT resources in a digital intelligent environment has emerged. This system utilizes cloud computing and IoT technology to simulate the behavior of intelligent devices and deep learning technology, achieving efficient resource scheduling. In addition, experimental data shows that the accuracy of the IoT resource cloud scheduling simulation system based on deep learning algorithm combined with digital intelligent environment is over 70%; the average task processing time is within 0.3 seconds; the average task response time is within 0.6 seconds. From this, it can be seen that combining deep learning algorithms with the system can quickly respond and solve problems, improving the reliability and stability of the system. The application range of this system is very wide, which can be used to optimize resource scheduling in many fields such as production, and can also be applied in fields such as smart home, smart medical, and intelligent transportation. With the continuous development of technology, this system would also be further improved and expanded to better serve people's lives and work.

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