{"title":"A Novel Framework to Enterprise Smart City with IOT and Analytics","authors":"K. Singamaneni, S. J. K. Reddy, U. Sreenivasulu","doi":"10.54216/jnfs.010104","DOIUrl":null,"url":null,"abstract":"The use of IoT devices like sensors, actuators, smartphones etc. is the very rapid and useful source in order to cope smartly with the public and community growth requirements. Nevertheless, when you connect thousands of IoT devices to create a smart network as you communicate over the Internet, you produce a massive amount of data, known as Big Data. Integrating IoT services to receive city data in real time and then efficiently processing large amounts of data to create a smart city is a challenge. Therefore, in this paper the smart town framework based on IoT using Big Data Analytics was proposed and developed. We use sensors such as smart home sensors , network cars, water and weather sensors, smart parking sensors, tracking objects, etc. The entire design and implementation model is proposed and implemented in a specific world using Hadoop ecosystems. The system is implemented in various steps , starting from data collection , aggregation, filtering, classification, preprocessing, computing and decision-making. Spark over Hadoop achieves reliability in the production of big data. The program is realistic for building smart cities by using intelligent systems as the city data base.","PeriodicalId":438286,"journal":{"name":"Journal of Neutrosophic and Fuzzy Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Neutrosophic and Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54216/jnfs.010104","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The use of IoT devices like sensors, actuators, smartphones etc. is the very rapid and useful source in order to cope smartly with the public and community growth requirements. Nevertheless, when you connect thousands of IoT devices to create a smart network as you communicate over the Internet, you produce a massive amount of data, known as Big Data. Integrating IoT services to receive city data in real time and then efficiently processing large amounts of data to create a smart city is a challenge. Therefore, in this paper the smart town framework based on IoT using Big Data Analytics was proposed and developed. We use sensors such as smart home sensors , network cars, water and weather sensors, smart parking sensors, tracking objects, etc. The entire design and implementation model is proposed and implemented in a specific world using Hadoop ecosystems. The system is implemented in various steps , starting from data collection , aggregation, filtering, classification, preprocessing, computing and decision-making. Spark over Hadoop achieves reliability in the production of big data. The program is realistic for building smart cities by using intelligent systems as the city data base.
物联网设备(如传感器、执行器、智能手机等)的使用是非常快速和有用的来源,以便巧妙地应对公众和社区的增长需求。然而,当你在互联网上通信时,连接数千个物联网设备来创建一个智能网络时,你会产生大量的数据,称为大数据。整合物联网服务以实时接收城市数据,然后高效处理大量数据以创建智慧城市是一项挑战。因此,本文提出并开发了基于物联网的大数据分析智慧城镇框架。我们使用传感器,如智能家居传感器、网络汽车、水和天气传感器、智能停车传感器、跟踪物体等。整个设计和实现模型是在使用Hadoop生态系统的特定世界中提出和实现的。该系统从数据采集、聚合、过滤、分类、预处理、计算和决策等多个步骤实现。Spark over Hadoop实现了大数据生产的可靠性。该方案以智能系统为城市数据库,实现了智慧城市的建设。