SMART CITY With IOT and BIG Data

Ajitpal Singh
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引用次数: 1

Abstract

The fast growth in the population density in urban areas demands more facilities and resources. To meet the needs of city development, the use of Internet of Things (IoT) devices and the smart systems is the very quick and valuable source. However, thousands of IoT devices are interconnecting and communicating with each other over the Internet results in generating a huge amount of data, termed as Big Data. To integrate IoT services and processing Big Data in an efficient way aimed at smart city is a challenging task. Therefore, in this paper, we proposed a system for smart city development based on IoT using Big Data Analytics. We use sensors deployment including smart home sensors, vehicular networking, weather and water sensors, smart parking sensor, and surveillance objects, etc. initially a four-tier architecture is proposed, which includes 1) Bottom Tier: which is responsible for IoT sources, data generations, and collections 2) Intermediate Tier-1: That is responsible for all type of communication between sensors, relays, base stations, the internet, etc. 3) Intermediate Tier 2: it is responsible for data management and processing using Hadoop framework, and 4) Top tier: is responsible for application and usage of the data analysis and results generated. The collected data from all smart system is processed at real-time to achieve smart cities using Hadoop with Spark, VoltDB, Storm or S4. We use existing datasets by various researchers including smart homes, smart parking weather, pollution, and vehicle for analysis and testing. All the datasets are replayed to test the real-time efficiency of the system. Finally, we evaluated the system by efficiency in term of throughput and processing.
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拥有物联网和大数据的智慧城市
城市人口密度的快速增长需要更多的设施和资源。为了满足城市发展的需求,使用物联网(IoT)设备和智能系统是非常快速和有价值的来源。然而,成千上万的物联网设备通过互联网相互连接和通信,从而产生了大量的数据,称为大数据。以智慧城市为目标,有效整合物联网服务和处理大数据是一项具有挑战性的任务。因此,在本文中,我们提出了一个基于物联网的基于大数据分析的智慧城市发展系统。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,智能停车传感器和监视对象等,最初提出了一个四层架构,其中包括1)底层:负责物联网来源,数据生成和收集2)中间层1:负责传感器,中继,基站,互联网等之间的所有类型的通信3)中间层2:负责使用Hadoop框架对数据进行管理和处理。4)Top layer:负责数据分析和生成结果的应用和使用。从所有智能系统收集的数据进行实时处理,使用Hadoop与Spark, voldb, Storm或S4实现智慧城市。我们使用各种研究人员的现有数据集,包括智能家居,智能停车天气,污染和车辆进行分析和测试。所有的数据集都被重放,以测试系统的实时效率。最后,我们从吞吐量和处理效率方面对系统进行了评估。
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