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Survey of Localization for Internet of Things Nodes: Approaches, Challenges and Open Issues

Author

Listed:
  • Sheetal Ghorpade

    (RMD Sinhgad School of Engineering, Savitribai Phule Pune University, Pune 411058, India)

  • Marco Zennaro

    (Science, Technology and Innovation Unit, International Centre for Theoretical Physics, 34151 Trieste, Italy)

  • Bharat Chaudhari

    (School of Electronics and Communication Engineering, MIT World Peace University, Pune 411037, India)

Abstract

With exponential growth in the deployment of Internet of Things (IoT) devices, many new innovative and real-life applications are being developed. IoT supports such applications with the help of resource-constrained fixed as well as mobile nodes. These nodes can be placed in anything from vehicles to the human body to smart homes to smart factories. Mobility of the nodes enhances the network coverage and connectivity. One of the crucial requirements in IoT systems is the accurate and fast localization of its nodes with high energy efficiency and low cost. The localization process has several challenges. These challenges keep changing depending on the location and movement of nodes such as outdoor, indoor, with or without obstacles and so on. The performance of localization techniques greatly depends on the scenarios and conditions from which the nodes are traversing. Precise localization of nodes is very much required in many unique applications. Although several localization techniques and algorithms are available, there are still many challenges for the precise and efficient localization of the nodes. This paper classifies and discusses various state-of-the-art techniques proposed for IoT node localization in detail. It includes the different approaches such as centralized, distributed, iterative, ranged based, range free, device-based, device-free and their subtypes. Furthermore, the different performance metrics that can be used for localization, comparison of the different techniques, some prominent applications in smart cities and future directions are also covered.

Suggested Citation

  • Sheetal Ghorpade & Marco Zennaro & Bharat Chaudhari, 2021. "Survey of Localization for Internet of Things Nodes: Approaches, Challenges and Open Issues," Future Internet, MDPI, vol. 13(8), pages 1-26, August.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:8:p:210-:d:615128
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    References listed on IDEAS

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    Cited by:

    1. Qiang Yang & Litao Hua & Xudong Gao & Dongdong Xu & Zhenyu Lu & Sang-Woon Jeon & Jun Zhang, 2022. "Stochastic Cognitive Dominance Leading Particle Swarm Optimization for Multimodal Problems," Mathematics, MDPI, vol. 10(5), pages 1-34, February.
    2. Roberto Saia & Salvatore Carta & Olaf Bergmann, 2021. "Wireless Internet, Multimedia, and Artificial Intelligence: New Applications and Infrastructures," Future Internet, MDPI, vol. 13(9), pages 1-3, September.
    3. Yasser Khan & Mazliham Bin Mohd Su’ud & Muhammad Mansoor Alam & Syed Fayaz Ahmad & Ahmad Y. A. Bani Ahmad (Ayassrah) & Nasir Khan, 2022. "Application of Internet of Things (IoT) in Sustainable Supply Chain Management," Sustainability, MDPI, vol. 15(1), pages 1-14, December.
    4. Jianmin Dang & Xiaozhen Wang & Ying Xie & Ziyi Fu, 2023. "The Location Optimization of Urban Shared New Energy Vehicles Based on P-Median Model: The Example of Xuzhou City, China," Sustainability, MDPI, vol. 15(12), pages 1-16, June.

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