Artificial intelligence in padel sport: Creation of an AI system

Detalhes bibliográficos
Autor(a) principal: Castro, João Rodrigo Ferreira Fernandes de
Data de Publicação: 2023
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/30751
Resumo: Padel is a sport that has been arousing everyone's curiosity and, therefore, the demand for it is high. More and more sports fields and venues have been built for the practice of this modality. As such, it is still an underexplored area in terms of Machine Learning technology and prediction models. It is possible to generate statistics in a Padel game, just like in other sports, and this dissertation proposes a strategy to develop a Machine Learning model to predict two movements relating to the game, namely Left Volleys and Trays. It is also essential to identify the trajectory of the ball in order to carry out a detailed analysis, as well as detect the lines of the padel court, in order to create an Artificial Intelligence system capable of predicting the movements made by the players and generating statistics on them. Thus, the general aim of this work is to design and develop a Machine Learning model to optimize the game of Padel, which together with the detection of the court and the identification of the ball, will generate the Artificial Intelligence system. The methodology is divided into three phases. The exploratory phase involves gathering information from the data and building data pipelines to extract insights, develop models, and test variables using feature engineering. This is followed by the AI modeling/automation phase to implement in the system. The third phase is analyzing the results to integrate AI into any real-time system.
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spelling Artificial intelligence in padel sport: Creation of an AI systemInteligência artificial -- Artificial intelligenceMachine learningPadelYOLOPadel is a sport that has been arousing everyone's curiosity and, therefore, the demand for it is high. More and more sports fields and venues have been built for the practice of this modality. As such, it is still an underexplored area in terms of Machine Learning technology and prediction models. It is possible to generate statistics in a Padel game, just like in other sports, and this dissertation proposes a strategy to develop a Machine Learning model to predict two movements relating to the game, namely Left Volleys and Trays. It is also essential to identify the trajectory of the ball in order to carry out a detailed analysis, as well as detect the lines of the padel court, in order to create an Artificial Intelligence system capable of predicting the movements made by the players and generating statistics on them. Thus, the general aim of this work is to design and develop a Machine Learning model to optimize the game of Padel, which together with the detection of the court and the identification of the ball, will generate the Artificial Intelligence system. The methodology is divided into three phases. The exploratory phase involves gathering information from the data and building data pipelines to extract insights, develop models, and test variables using feature engineering. This is followed by the AI modeling/automation phase to implement in the system. The third phase is analyzing the results to integrate AI into any real-time system.O Padel é um desporto que tem vindo a despertar a curiosidade de todos e, por isso, a procura pelo mesmo é elevada. Cada vez mais têm sido construídos campos e recintos desportivos para a prática desta modalidade. Como tal, é uma área ainda pouco explorada no que toca à tecnologia e aos modelos de previsão de Machine Learning. É possível gerar estatísticas num jogo de Padel, tal como acontece noutras modalidades, e esta dissertação propõe uma estratégia para desenvolver um modelo de Machine Learning, de modo a prever dois movimentos referentes ao jogo, nomeadamente, os Left Volleys e as Bandejas. Também é fundamental identificar a trajetória da bola para fazer uma análise pormenorizada, assim como detetar as linhas do campo de Padel, de forma a criar um sistema de Inteligência Artificial capaz de prever os movimentos feitos pelos jogadores e gerar estatísticas do mesmo. Assim, o objetivo geral deste trabalho é conceber e desenvolver um modelo de Machine Learning para otimizar o jogo de Padel, que juntamente com a deteção do campo e com a identificação da bola, irá constituir o sistema de Inteligência Artificial. A metodologia divide-se em três fases. A fase exploratória que diz respeito à recolha de informação dos dados e à construção de pipelines de dados para extrair insights, desenvolver modelos e testar variáveis utilizando feature engineering. Em seguida, a fase de modelação/automação da IA para implementar no sistema. A terceira fase corresponde à análise de resultados para integrar a IA em qualquer sistema em tempo-real.2024-01-31T16:04:14Z2023-12-07T00:00:00Z2023-12-072023-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10071/30751TID:203467990engCastro, João Rodrigo Ferreira Fernandes deinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-04T01:21:46Zoai:repositorio.iscte-iul.pt:10071/30751Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:08:08.703309Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Artificial intelligence in padel sport: Creation of an AI system
title Artificial intelligence in padel sport: Creation of an AI system
spellingShingle Artificial intelligence in padel sport: Creation of an AI system
Castro, João Rodrigo Ferreira Fernandes de
Inteligência artificial -- Artificial intelligence
Machine learning
Padel
YOLO
title_short Artificial intelligence in padel sport: Creation of an AI system
title_full Artificial intelligence in padel sport: Creation of an AI system
title_fullStr Artificial intelligence in padel sport: Creation of an AI system
title_full_unstemmed Artificial intelligence in padel sport: Creation of an AI system
title_sort Artificial intelligence in padel sport: Creation of an AI system
author Castro, João Rodrigo Ferreira Fernandes de
author_facet Castro, João Rodrigo Ferreira Fernandes de
author_role author
dc.contributor.author.fl_str_mv Castro, João Rodrigo Ferreira Fernandes de
dc.subject.por.fl_str_mv Inteligência artificial -- Artificial intelligence
Machine learning
Padel
YOLO
topic Inteligência artificial -- Artificial intelligence
Machine learning
Padel
YOLO
description Padel is a sport that has been arousing everyone's curiosity and, therefore, the demand for it is high. More and more sports fields and venues have been built for the practice of this modality. As such, it is still an underexplored area in terms of Machine Learning technology and prediction models. It is possible to generate statistics in a Padel game, just like in other sports, and this dissertation proposes a strategy to develop a Machine Learning model to predict two movements relating to the game, namely Left Volleys and Trays. It is also essential to identify the trajectory of the ball in order to carry out a detailed analysis, as well as detect the lines of the padel court, in order to create an Artificial Intelligence system capable of predicting the movements made by the players and generating statistics on them. Thus, the general aim of this work is to design and develop a Machine Learning model to optimize the game of Padel, which together with the detection of the court and the identification of the ball, will generate the Artificial Intelligence system. The methodology is divided into three phases. The exploratory phase involves gathering information from the data and building data pipelines to extract insights, develop models, and test variables using feature engineering. This is followed by the AI modeling/automation phase to implement in the system. The third phase is analyzing the results to integrate AI into any real-time system.
publishDate 2023
dc.date.none.fl_str_mv 2023-12-07T00:00:00Z
2023-12-07
2023-10
2024-01-31T16:04:14Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/30751
TID:203467990
url http://hdl.handle.net/10071/30751
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dc.language.iso.fl_str_mv eng
language eng
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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