Computational intelligence, machine learning techniques, and IOT

K. Vijayakumar
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引用次数: 10

Abstract

In the current scenario, automated approaches are widely adopted in various domains to implement the computerized monitoring and regulation. The massive advancement in the machine-driven technologies such as computational intelligence, machine-learning scheme, deep-learning scheme, and the Internet of Things (IoT) helped to advance the industrial automation to the next level, in which the automated detection and classification is easily implemented. Computerized systems are essential in a variety of domains to achieve an error free monitoring and the control without compromising the accuracy. Further, the availability of advanced computational facilities helps to achieve superior outcomes, in a variety of domains, such as industry, manufacturing, agriculture, medical, and other engineering and science domains. The integration of traditional approach with the recent computational intelligence technique also helps to achieve a better result during the problem solving practice. The integration of the recent approach along with the IoT helped to automate the entire system using the current internet technology and also supports the remote monitoring and control. When an industry is equipped with all these facility is also called as an industry ready with the essential future enhancement essential to implement ‘‘Industry 4.0’’ an essential keyword to indicate the present trend of automation and data exchange in industries which includes; cyber-physical systems, IoT, cloud computing, and cognitive computing with essential smart facilities.
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计算智能、机器学习技术和物联网
在目前的情况下,自动化的方法在各个领域被广泛采用,以实现计算机化的监控和监管。计算智能、机器学习方案、深度学习方案和物联网(IoT)等机器驱动技术的巨大进步有助于将工业自动化推进到一个新的水平,其中自动检测和分类很容易实现。计算机化系统在各种领域中都是必不可少的,以实现无误差的监测和控制,而不影响精度。此外,先进计算设施的可用性有助于在各种领域(如工业、制造业、农业、医疗以及其他工程和科学领域)取得卓越的成果。将传统方法与最新的计算智能技术相结合,也有助于在实际问题求解中取得更好的结果。最近的方法与物联网的集成有助于使用当前的互联网技术实现整个系统的自动化,并且还支持远程监控。当一个行业配备了所有这些设施时,也被称为一个行业准备好了必要的未来增强,这是实施“工业4.0”所必需的,这是一个关键字,用于指示当前行业自动化和数据交换的趋势,其中包括;网络物理系统、物联网、云计算和认知计算具有必要的智能设施。
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