IDEAS home Printed from https://ideas.repec.org/a/tec/sustai/ojs13648.html

Smart Crowd RAN: An AI-Driven Network Capacity and Congestion-Mitigation Framework for Saudi Mega-Events — Riyadh Season, Expo 2030, and FIFA World Cup 2034

Author

Listed:
  • Mohammad Firoz

    (Independent Researcher – Advanced Technologies Network Performance Specialist, Riyadh (KSA))

Abstract

Saudi Arabia is entering an unprecedented decade of mega-events. Hajj continues annually with more than two million pilgrims concentrated in approximately ten square kilometres of Makkah and Madinah. Riyadh Season draws 18 million-plus visitors over a four-month run. LEAP, the Kingdom's flagship technology event, attracts more than 200,000 attendees in a single week. AFC Asian Cup 2027 will be held across multiple Saudi cities. Expo 2030 in Riyadh is officially registered with the Bureau International des Expositions, scheduled to run from 1 October 2030 to 31 March 2031, expecting more than 40 million visitors and 197 participating nations on a six-million-square-metre site. FIFA World Cup 2034 — confirmed on 11 December 2024 — will be hosted across 15 stadiums in 5 cities (Riyadh, Jeddah, Al Khobar, NEOM, and Abha), with capacities ranging from 45,000 to 92,760, a $20 billion-plus stadium investment, and an expected influx of more than five million international visitors. This combination of events is unique globally. No other country has scheduled this density of mega-events on this scale within the same decade. The implication for telecommunications is profound. Each event places extreme, concentrated, and time-bound load on the cellular network. Hajj 2024 demonstrated what is possible: stc and Nokia delivered the world's first live deployment of cognitive AI-driven SON (MantaRay), processing more than 10,000 autonomous actions in 15-minute optimization intervals, lifting loaded-cell utilization by approximately 30 percent, improving user throughput by about 10 percent on average, and holding service quality steady through a 40 percent traffic surge for over a million pilgrims (Nokia, 2024). That deployment is the empirical anchor on which this paper builds. This paper proposes Smart Crowd RAN, an AI-driven network capacity and congestion-mitigation framework specifically designed for the Saudi mega-event context. The framework introduces two coined sub-components: CrowdSense-RAN, a multi-modal data fusion engine that combines computer-vision crowd density (CCTV), IoT sensors (turnstiles, transit), ticket-sales nowcasting, and weather/transit feeds to forecast cell-load patterns 15 minutes to 4 hours ahead; and MegaEvent-RAN-KSA, a four-layer reference architecture that orchestrates network slicing, drone-cell deployment, COW/CoLT pre-staging, and reinforcement-learning-driven xApps over multi-vendor 5G Standalone networks. The framework extends RIC-SON-KSA from earlier work into surge-mode operations and integrates with ALLaM-NetOps for sovereign GenAI-driven NetOps narration. The methodology integrates literature review of crowd-aware RAN, network slicing, and AI-driven capacity planning (2020 to 2026); real Saudi mega-event milestones from CST, GACA, the Royal Commission for Riyadh City, NEOM TONOMUS, and Saudi 2034 bid-book disclosures; and analytical projection of Smart Crowd RAN performance using the real Hajj 2024 MantaRay outcomes as the empirical baseline plus published gain ranges from 5G mega-event literature (Qatar 2022 World Cup digital twin, Tokyo 2020 Olympics 5G deployments, Paris 2024 Olympics, Vodafone EURO 2024). Findings indicate four things. First, the demand profile of Saudi mega-events is fundamentally different from steady-state network operations and requires forecast-driven capacity orchestration rather than reactive optimization alone. Second, network slicing — eMBB for fan video, URLLC for public safety and operations, mMTC for IoT, V2X for smart transport — is the single highest-leverage capacity-mitigation lever available, and Saudi operators already have the 5G SA spectrum (post-November 2024 auction: stc 516 MHz, Mobily 460 MHz, Zain 370 MHz) to deploy it. Third, drone-cell augmentation, COW/CoLT pre-staging, and fan-zone small cells form a complementary capacity stack that can deliver 50 percent or more incremental capacity over baseline macro coverage. Fourth, Saudi mega-events offer Saudi operators a globally unique opportunity to lead the world in mega-event RAN engineering — much as Qatar 2022 led on stadium digital twins. The paper concludes that the next decade of Saudi telecommunications excellence will not be defined by routine network operations but by the Kingdom's ability to deliver flawless connectivity at the world's most-watched events. Smart Crowd RAN gives the Kingdom a structured, AI-native, multi-vendor blueprint for that mega-event excellence, aligned with Saudi Vision 2030 and ready to scale from Hajj 2026 through Expo 2030 to FIFA World Cup 2034.

Suggested Citation

  • Mohammad Firoz, 2026. "Smart Crowd RAN: An AI-Driven Network Capacity and Congestion-Mitigation Framework for Saudi Mega-Events — Riyadh Season, Expo 2030, and FIFA World Cup 2034," Technium Sustainability, Technium Science, vol. 11, pages 75-96, May.
  • Handle: RePEc:tec:sustai:ojs:13648
    DOI: 10.47577/sustainability.v11i.13648
    as

    Download full text from publisher

    File URL: https://techniumscience.com/index.php/sustainability/article/view/13648
    Download Restriction: no

    File URL: https://libkey.io/10.47577/sustainability.v11i.13648?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tec:sustai:ojs:13648. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Tasente Tanase The email address of this maintainer does not seem to be valid anymore. Please ask Tasente Tanase to update the entry or send us the correct address (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.