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IoT-based smart city development using big data analytical approach

机译:大数据分析方法的基于物联网的智慧城市发展

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To meet the needs of urban public and the city development smartly, the use of IoT devices, such as sensors, actuators, and smartphones, etc., and the smart system is the very fast and valuable source. However, interconnecting thousands of IoT devices while communicating with each other over the Internet to establish a smart system, results in the generation of huge amount of data, termed as Big Data. To integrate IoT services in order to get real-time city data and then processing such big amount of data in an efficient way aimed at establishing smart city is a challenging task. Therefore, in this paper, we proposed and developed a smart city system based on IoT using Big Data Analytics. We use sensors deployment including smart home sensors, vehicular networking, weather and water sensors, smart parking sensors, surveillance objects, etc. The complete architecture and implementation model is proposed, which is implemented using Hadoop ecosystem in a real environment. The system implementation consists of various steps that start from data generation and collecting, aggregating, filtration, classification, preprocessing, computing and finished at decision making. The efficiency in Big Data processing is achieved using spark over Hadoop. The system is practically implemented by taken smart systems as city data source to develop smart city. The evaluation results show that the proposed system is scalable and efficient.
机译:为了智能地满足城市公众和城市发展的需求,使用物联网设备(例如传感器,执行器和智能手机等)以及智能系统是非常快速和有价值的资源。但是,在通过Internet相互通信以建立智能系统的同时互连数千个IoT设备会导致生成大量数据,称为大数据。集成物联网服务以获取实时城市数据,然后以建立智慧城市的有效方式处理如此大量的数据是一项艰巨的任务。因此,在本文中,我们使用大数据分析提出并开发了一个基于物联网的智能城市系统。我们使用传感器部署,包括智能家居传感器,车载网络,天气和水传感器,智能停车传感器,监视对象等。提出了完整的架构和实现模型,该模型和实现模型是在真实环境中使用Hadoop生态系统实现的。系统实现包括从数据生成和收集,汇总,过滤,分类,预处理,计算到决策制定的各个步骤。大数据处理的效率是通过Hadoop上的Spark实现的。该系统实际上是以智能系统为城市数据源,以发展智能城市而实现的。评估结果表明,该系统具有良好的扩展性和有效性。

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