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IoT-Based Big Data: From Smart City towards Next Generation Super City Planning

Author

Listed:
  • M. Mazhar Rathore

    (School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea)

  • Anand Paul

    (School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea)

  • Awais Ahmad

    (School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea)

  • Gwanggil Jeon

    (Department of Embedded Systems Engineering, Incheon National University, Incheon, South Korea)

Abstract

Recently, a rapid growth in the population in urban regions demands the provision of services and infrastructure. These needs can be come up wit the use of Internet of Things (IoT) devices, such as sensors, actuators, smartphones and smart systems. This leans to building Smart City towards the next generation Super City planning. However, as thousands of IoT devices are interconnecting and communicating with each other over the Internet to establish smart systems, a huge amount of data, termed as Big Data, is being generated. It is a challenging task to integrate IoT services and to process Big Data in an efficient way when aimed at decision making for future Super City. Therefore, to meet such requirements, this paper presents an IoT-based system for next generation Super City planning using Big Data Analytics. Authors have proposed a complete system that includes various types of IoT-based smart systems like smart home, vehicular networking, weather and water system, smart parking, and surveillance objects, etc., for dada generation. An architecture is proposed that includes four tiers/layers i.e., 1) Bottom Tier-1, 2) Intermediate Tier-1, 3) Intermediate Tier 2, and 4) Top Tier that handle data generation and collections, communication, data administration and processing, and data interpretation, respectively. The system implementation model is presented from the generation and collection of data to the decision making. The proposed system is implemented using Hadoop ecosystem with MapReduce programming. The throughput and processing time results show that the proposed Super City planning system is more efficient and scalable.

Suggested Citation

  • M. Mazhar Rathore & Anand Paul & Awais Ahmad & Gwanggil Jeon, 2017. "IoT-Based Big Data: From Smart City towards Next Generation Super City Planning," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 13(1), pages 28-47, January.
    • Handle: RePEc:igg:jswis0:v:13:y:2017:i:1:p:28-47
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    Citations

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    Cited by:

    1. Shaohua Wang & Xianxiong Liu & Haiyin Wang & Qingwu Hu, 2018. "A Case Study on Spatio-Temporal Data Mining of Urban Social Management Events Based on Ontology Semantic Analysis," Sustainability, MDPI, vol. 10(6), pages 1-24, June.
    2. Johan Meppelink & Jens Van Langen & Arno Siebes & Marco Spruit, 2020. "Beware Thy Bias: Scaling Mobile Phone Data to Measure Traffic Intensities," Sustainability, MDPI, vol. 12(9), pages 1-19, May.
    3. Soumya J. Bhat & K. V. Santhosh, 2022. "Localization of isotropic and anisotropic wireless sensor networks in 2D and 3D fields," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 79(2), pages 309-321, February.
    4. Rehman Abdul & Anand Paul & Junaid Gul M. & Won-Hwa Hong & Hyuncheol Seo, 2018. "Exploiting Small World Problems in a SIoT Environment," Energies, MDPI, vol. 11(8), pages 1-18, August.
    5. Zhanxue Gong & Xiyuan Li & Jiawen Liu & Yeming Gong, 2019. "Machine learning in explaining nonprofit organizations’ participation : a driving factors analysis approach," Post-Print hal-02880932, HAL.
    6. Nikhlesh Pathik & Rajeev Kumar Gupta & Yatendra Sahu & Ashutosh Sharma & Mehedi Masud & Mohammed Baz, 2022. "AI Enabled Accident Detection and Alert System Using IoT and Deep Learning for Smart Cities," Sustainability, MDPI, vol. 14(13), pages 1-24, June.
    7. Eunbee Gil & Yongjin Ahn & Youngsang Kwon, 2020. "Tourist Attraction and Points of Interest (POIs) Using Search Engine Data: Case of Seoul," Sustainability, MDPI, vol. 12(17), pages 1-21, August.
    8. Johannes Stübinger & Lucas Schneider, 2020. "Understanding Smart City—A Data-Driven Literature Review," Sustainability, MDPI, vol. 12(20), pages 1-23, October.

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