Home Automation Using AI and IoT

K. D. Patil, Liladhar Gaikwad, Sujit Bhoite, Aditya Tajane, D. D. Kulkarni
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Abstract

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.
利用人工智能和物联网实现家庭自动化
物联网网络的海量数据流和存储可以通过人工智能轻松管理。由于高速互联网络的发展和一些可集成到微控制器中的尖端传感器,物联网目前正变得越来越流行。目前在互联网上流动的数据包括从工作站发送和接收的用户数据以及传感器数据。由于工作站和众多传感器数量的增加,较少的数据可能确实会在存储方面、延迟、信道限制和网络内部窒息等方面遇到挑战。在过去十年中,已经提出了几种算法来防止这些问题。人工智能仍然是唯一一种除了挖掘信息外还能管理和调节网络拥塞的算法。本文旨在展示人工智能系统在物联网中的应用。研究强调了信息管理和挖掘的重要性。此外,本研究还将结合物联网网络研究合成智能中使用的方法,如模糊逻辑或神经网络。指定网络和自修改网络中的软件是人工智能物联网系统中的一些重要参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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