IoT Based Weather Monitoring System for Smart Cities: A Comprehensive Review

Samriddhi Banara, T. Singh, Anamika Chauhan
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引用次数: 2

Abstract

The Internet of Things (IoT) is a new paradigm that aspires to integrate all smart physical things such that they will always give smart and cognitive solutions to people. Internet of things (IoT) plays a significant role in the evolution of applications in different fields such as health, education, smart cities, homes, agriculture, and so on in the current era of research and technology. The IoT ecosystem is examined in this article. All of the components of the Internet of Things, as well as their significance, have been discussed in detail. Climate monitoring systems have improved in extensive features as a result of the rapid growth of technology and the competitive technological revolution. Climate change and environmental monitoring have recently got quite a bit of attention. Man desires to be informed on the most recent weather conditions of any location. Because the globe is evolving at such a rapid pace, so should weather monitoring stations. This paper presents the literature review of the existing weather Monitoring System, types of sensors, micro-controller and communication medium used. With the help of this research, we aim to diversify weather monitoring system frameworks with the internet of things in the long term and to improve the results with knowledge and comprehension from the rapid development of digital learning research, such as low-cost sensors and renewable energy sources, under which two dominant systems interact against one another and, one to create more precise information and another to forecast the condition.
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基于物联网的智慧城市天气监测系统综述
物联网(IoT)是一种新的范式,它渴望整合所有智能物理事物,以便它们始终为人们提供智能和认知的解决方案。在当今的研究和技术时代,物联网(IoT)在健康、教育、智慧城市、家庭、农业等不同领域的应用演变中发挥着重要作用。本文将研究物联网生态系统。详细讨论了物联网的所有组成部分及其意义。由于技术的快速发展和竞争性的技术革命,气候监测系统的广泛性得到了改善。气候变化和环境监测最近得到了相当多的关注。人们希望了解任何地点的最新天气情况。因为地球正在以如此快的速度发展,天气监测站也应该如此。本文介绍了现有天气监测系统的文献综述,传感器的类型,微控制器和通信介质的使用。在本研究的帮助下,我们的目标是通过物联网长期多样化天气监测系统框架,并通过快速发展的数字学习研究(如低成本传感器和可再生能源)的知识和理解来改善结果,在这些研究中,两个主导系统相互作用,一个创建更精确的信息,另一个预测条件。
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