Abstract

Artificial Intelligence has introduced a new approach to how sports event timing services and participant verification are handled. By applying AI and machine learning solutions alongside RFID race timing systems and computer vision, timing operations now rely on automated identification and structured data handling. This approach supports race timing technology in India by linking participant records, visual inputs, and timing data into a single workflow

Across endurance formats, the use of Artificial Intelligence together with UHF RFID race timing supports marathon & running event timing solutions and participant verification tasks. These implementations highlight how AI contributes to organised timing processes and participant data review across competitive environments

Problem

In large participation events, RFID chip timing for athletes is widely used to capture timing data. While ultra-high frequency (UHF) RFID timing records participant movement, confirming that the registered participant is the individual wearing the tag can be difficult at scale.

Such mismatches affect electronic athlete identification and interfere with race timing and results management. Without AI-assisted validation, managing identity checks alongside timing data becomes increasingly complex as event size grows.

Solution

Artificial Intelligence supports event day management solutions by analysing visual data and aligning it with RFID athlete tracking records. Through computer vision techniques, participant bib details are compared with stored registration data, allowing identity checks to be carried out during the event.

This setup combines facial analysis methods with UHF chip timing for running races, helping organisers review participant movement and timing records together. The process supports professional race timing services by assisting with participant verification and timing oversight throughout the course.

Pre-Event Preparation

Participant information setup: Registration details are stored within systems supporting automated participant tracking system workflows.

Identifier allocation: Participants receive RFID bib tags and shoe tags linked to their registration records.

Central data management: Participant information is maintained within platforms supporting race timing technology in India and identification review.

AI-Based Tracking System

Computer vision analysis: AI models process event footage to assist with participant identification.

Biometric identification systems: Facial data is matched with registration records to support identity checks.

RFID integration: Passive RFID tracking for sports connects timing records with participant data through readers placed along the course.

Data handling workflows: Event data supports online race results publishing and timing record review.

Conclusion

The use of Artificial Intelligence alongside RFID race timing systems has changed how participant identity and timing data are handled together. By combining biometric validation for race timing with chip-based identification, organisers gain better oversight of participant records across endurance events.

Through race timing services in India, and AI-supported identification methods, timing operations and participant verification are managed with greater consistency across large-scale events.