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Research on the General Algorithm and Benefit of Real-Time Positioning Advertising System—Based on the Use of 5G Base Station Data

Author

Listed:
  • Wei-Min Cheng

    (Doctoral Program in Design, College of Design, National Taipei University of Technology, Taipei 10608, Taiwan)

  • Sheng-Ming Wang

    (Department of Interaction Design, National Taipei University of Technology, Taipei 10608, Taiwan)

Abstract

Due to the limitations of mobile phone positioning technology in the past, it is difficult for an advertising system to obtain users’ locations. Although there are many advertising delivery ideas in the market, time and location-based advertising delivery system have not been able to meet the delivery needs of advertisers. This study investigates various time and location-based advertising needs in the market and finds a universal data processing model that can quickly organize user positioning data from telecom base stations into screening information. It helps us to find specific audiences and to deliver advertisements to target audiences quickly. This study evaluated various advertising scenarios’ effectiveness and explained why there is a performance gap usually between five to ten times worse compared to the past. This study discusses the problems encountered when implementing the advertising system and how to improve them. This study also examines advertising interaction methods based on 5G features, business cooperation and profit splitting with telecom operators, and more diversified data application orientations and possibilities such as market surveys, urban traffic, security issues, and epidemic prevention. The future challenge is to develop footprint tracking technologies based on 5G and provide smart cities with lives-protecting or cost-saving solutions.

Suggested Citation

  • Wei-Min Cheng & Sheng-Ming Wang, 2021. "Research on the General Algorithm and Benefit of Real-Time Positioning Advertising System—Based on the Use of 5G Base Station Data," Future Internet, MDPI, vol. 13(8), pages 1-23, July.
    • Handle: RePEc:gam:jftint:v:13:y:2021:i:8:p:187-:d:598887
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    References listed on IDEAS

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    1. Lehr, William & Queder, Fabian & Haucap, Justus, 2021. "5G: A new future for Mobile Network Operators, or not?," Telecommunications Policy, Elsevier, vol. 45(3).
    2. Jie Hou & Baizhou Li, 2020. "The Evolutionary Game for Collaborative Innovation of the IoT Industry under Government Leadership in China: An IoT Infrastructure Perspective," Sustainability, MDPI, vol. 12(9), pages 1-21, May.
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    Cited by:

    1. Shi, Baisheng & Wang, Hao, 2023. "An AI-enabled approach for improving advertising identification and promotion in social networks," Technological Forecasting and Social Change, Elsevier, vol. 188(C).

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