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The IoT network's massive data flows and storage can be easily managed with AI. IoT is currently growing more and more popular because to the development of high-speed internet networks and several cutting-edge sensors that can be incorporated into microcontrollers. The data that is now flowing across the internet includes user data that is sent and received from workstations as well as sensor data. Fewer data may really be experiencing challenges on the storage side, latency, channels limitation, and suffocation inside the networks due to the increase in the number of workstations and numerous sensors. Over the past ten years, several algorithms have been presented to prevent these issues. AI is still the only algorithm that can manage and regulate network congestion in addition to mining information. This paper's purpose is to demonstrate how an AI system is being used in the Internet of Things. The study emphasizes the significance of information management and mining. Additionally, the approach used in synthetic intelligence, such as fuzzy logics or neural networks, will be examined in this study in relation to IoT network. The software in specified networks and self-modifying networks are some of the essential parameters in the AI IoT system.
Patil et al. (Mon,) studied this question.