DISTRIBUTED INTELLIGENCE APPLIED TO STREET RACING: A MULTIAGENCY APPROACH
DOI:
https://doi.org/10.63330/sasciencesv6n2-212Keywords:
Distributed Intelligence, IoT, Machine Learning, Multiagent Systems, Sports Logistics ManagementAbstract
The main objective of this study, of an exploratory and descriptive nature, is to propose and evaluate a multi-agent system architecture applied to road running, focusing on athlete monitoring and logistics management. The methodology involved the modeling of four agents—namely athlete, coach, organizer, and medical doctor—in a distributed environment, integrating IoT sensors and machine learning algorithms. The simulation with 100 participants demonstrated greater efficiency in data collection, optimization of support logistics, and the issuance of preventive medical alerts. It is concluded that the multi-agent approach represents a promising solution for mass sporting events, enhancing athlete safety and experience, in addition to opening perspectives for future integration with smart cities and advanced reinforcement learning techniques.
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