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Nusuk Card System


Added by:   OECD analyst
Added on:   11 Sep 2026
Updated by:   OECD analyst
Updated on:   11 Sep 2026

The Nusuk Card System is a comprehensive IoT and AI-driven crowd management initiative designed to facilitate and secure the Hajj journey for over 1.8 million pilgrims. By utilising RFID-enabled smart cards and a network of over 800 surveillance cameras equipped with AI analytics across the Holy Sites, the system tracks pilgrim movements, ensures adherence to scheduling plans, and prevents overcrowding.

Name in original language

نظام بطاقة نسك

Initiative overview

The Nusuk Card System seeks to resolve the immense logistical and safety challenges associated with managing over 1.8 million pilgrims within the geographically constrained areas of the Holy Sites (Mina, Arafat, Muzdalifah, and the Jamarat facility) during the Hajj season. The primary opportunity it leverages is the integration of Internet of Things (IoT) technologies, specifically RFID (Radio Frequency Identification), with advanced Artificial Intelligence (AI) video analytics. The core objectives are to verify pilgrim identities seamlessly, monitor real-time locations, ensure service providers (Hajj companies) comply with strict dispatching schedules, and proactively manage crowd flows to prevent life-threatening bottlenecks or counter-flow movements.

The initiative operates by issuing every pilgrim an RFID-enabled Nusuk Card, which serves as their official identification and access pass. As pilgrims move through camps and pathways, strategically placed RFID readers capture their data. This is complemented by a network of over 800 AI-powered cameras installed at entrances, corridors, and critical choke points like the Jamarat building. The AI system analyses the camera feeds to perform headcounts, detect anomalies such as pilgrims moving against the designated flow, and predict potential congestion points before they escalate into critical incidents.

Looking to the future, the initiative is expected to scale significantly. While implemented on a limited basis previously, it is undergoing massive expansion for the 2025 Hajj season. The system aims to build predictive indicators for various scenarios, such as the housing of pilgrims from different nationalities in adjacent camps, and to track the complete journey of a pilgrim by calculating readings between different points. This will institutionalise data-driven decision-making within the Ministry of Hajj and Umrah, allowing for dynamic, real-time adjustments to crowd management strategies and improving the overall experience and safety of the pilgrims.

Results, outcomes and impacts
The Nusuk Card System has demonstrated significant potential in enhancing crowd management and pilgrim safety. By integrating RFID tracking with AI camera headcounts, the Ministry has been able to calculate the precise percentages of pilgrims moving between different points, providing a comprehensive view of the pilgrim journey. The system has enabled real-time monitoring of service companies, ensuring their adherence to updated dispatch plans and schedules based on analysed data. This proactive approach has facilitated the early detection of anomalies, such as counter-flow movements, allowing authorities to intervene swiftly and prevent dangerous bottlenecks. As the system expands in the upcoming season, it is expected to yield even more.

Other relevant details

Challenges and lessons learned: The development and implementation of the Nusuk Card System presented several notable challenges. A primary technical hurdle was ensuring reliable RFID readability of the Nusuk cards amidst massive, dense crowds. To mitigate this risk, the team innovatively compensated for missed RFID reads by deploying AI-powered headcounting through the network of over 800 cameras, creating a robust, multi-layered tracking system. Another significant challenge involved network coverage across the expansive and geographically complex Holy Sites, which is critical for real-time data transmission. Furthermore, building accurate predictive indicators for complex scenarios—such as managing the dynamics of housing pilgrims from diverse nationalities in adjacent camps—required sophisticated data modeling. Operationally, ensuring that the various service-providing companies strictly adhered to the dynamically updated dispatch plans and schedules, which were generated based on real-time analyzed data, proved

About the policy initiative


Category:

  • AI policy initiatives, programmes and projects

Initiative type:

  • AI use cases/projects in the public sector

Status:

  • Active

Start Year:

  • 2024

OECD AI Principles: