A bibliography experiment on research within the scope of industry 4.0 application areas in sports: Sporda endüstri 4.0 uygulama alanları kapsamında yapılan araştırmalar üzerine bir bibliyografya denemesi

Developed countries develop their production sites within the scope of industry 4.0 technology components and experience constant change and transformation to establish economic superiority. This situation allows them to produce more in various fields and thus to rise to a more advantageous position economically. Industry 4.0 technology affects areas within the scope of the sports industry such as sports tourism, athlete performance, athlete health, sports publishing, sports textile products, sports education and training, sports management and human resources, and creates an international competition environment in terms of production and performance. In this study, it is aimed to examine the researches about the usage areas of industry 4.0 in sports. From this point on, researches in the context of the subject have been presented with bibliographic method. In the conclusion section, the weaknesses and possibilities of youth sociology were discussed, and efforts were made to present a projection on what to do about the field. In this respect, a youth sociology evaluation has been tried to be made on the prominent topics, forgotten aspects and themes left incomplete in youth sociology studies. ​Extended English summary is in the end of Full Text PDF (TURKISH) file.   Özet Gelişmiş ülkeler endüstri 4.0 teknolojisi bileşenleri kapsamında üretim sahalarını geliştirmekte ve ekonomik üstünlük kurmak amacıyla sürekli değişim ve dönüşüm yaşamaktadır. Bu durum onların çeşitli alanlarda daha fazla üretmelerine dolayısıyla ekonomik yönden daha avantajlı konuma yükselmelerine olanak sağlamaktadır. Endüstri 4.0 teknolojisi spor turizmi, sporcu performansı, sporcu sağlığı, spor yayıncılığı, spor tekstil ürünleri, spor eğitimi ve öğretimi, spor yönetimi ve insan kaynakları gibi spor endüstrisi kapsamındaki alanları etkilemekte üretim ve performans yönünden ülkeler arası bir rekabet ortamı oluşturmaktadır. Bu çalışmada endüstri 4.0’ın sporda kullanım alanları ile ilgili araştırmaların incelenmesi hedeflenmektedir. Bu noktadan hareketle konu bağlamındaki araştırmalar bibliyografik metodla ortaya konmuştur. Sonuç bölümünde ise sporda endüstri 4.0 kullanım alanları tartışılmış, alana olan katkıları ve olumuz etkilerinin değerlendirilmesi yapılmıştır. &nbsp

Adaptive action supervision in reinforcement learning from real-world multi-agent demonstrations

Modeling of real-world biological multi-agents is a fundamental problem in various scientific and engineering fields. Reinforcement learning (RL) is a powerful framework to generate flexible and diverse behaviors in cyberspace; however, when modeling real-world biological multi-agents, there is a domain gap between behaviors in the source (i.e., real-world data) and the target (i.e., cyberspace for RL), and the source environment parameters are usually unknown. In this paper, we propose a method for adaptive action supervision in RL from real-world demonstrations in multi-agent scenarios. We adopt an approach that combines RL and supervised learning by selecting actions of demonstrations in RL based on the minimum distance of dynamic time warping for utilizing the information of the unknown source dynamics. This approach can be easily applied to many existing neural network architectures and provide us with an RL model balanced between reproducibility as imitation and generalization ability to obtain rewards in cyberspace. In the experiments, using chase-and-escape and football tasks with the different dynamics between the unknown source and target environments, we show that our approach achieved a balance between the reproducibility and the generalization ability compared with the baselines. In particular, we used the tracking data of professional football players as expert demonstrations in football and show successful performances despite the larger gap between behaviors in the source and target environments than the chase-and-escape task.Comment: 14 pages, 5 figure

Data-Driven Analytics for Decision Making in Game Sports

Performance analysis and good decision making in sports is important to maximize chances of winning. Over the last years the amount and quality of data which is available for the analysis has increased enormously due to technical developments like, e.g., of sensor technologies or computer vision technology. However, the data-driven analysis of athletes and team performances is very demanding. One reason is the so called semantic gap of sports analytics. This means that the concepts of coaches are seldomly represented in the data for the analysis. Furthermore, sports in general and game sports in particular present a huge challenge due to its dynamic characteristics and the multi-factorial influences on an athlete’s performance like, e.g., the numerous interaction processes during a match. This requires different types of analyses like, e.g., qualitative analyses and thus anecdotal descriptions of performances up to quantitative analyses with which performances can be described through statistics and indicators. Additionally, coaches and analysts have to work under an enormous time pressure and decisions have to be made very quickly. In order to facilitate the demanding task of game sports analysts and coaches we present a generic approach how to conceptualize and design a Data Analytics System (DAS) for an efficient support of the decision making processes in practice. We first introduce a theoretical model and present a way how to bridge the semantic gap of sports analytics. This ensures that DASs will provide relevant information for the decision makers. Moreover, we show that DASs need to combine qualitative and quantitative analyses as well as visualizations. Additionally, we introduce different query types which are required for a holistic retrieval of sports data. We furthermore show a model for the user-centered planning and designing of the User Experience (UX) of a DAS. Having introduced the theoretical basis we present SportSense, a DAS to support decision making in game sports. Its generic architecture allows a fast adaptation to the individual characteristics and requirements of different game sports. SportSense is novel with respect to the fact that it unites raw data, event data, and video data. Furthermore, it supports different query types including an intuitive sketch-based retrieval and seamlessly combines qualitative and quantitative analyses as well as several data visualization options. Moreover, we present the two applications SportSense Football and SportSense Ice Hockey which contain sport-specific concepts and cover (high-level) tactical analyses

Multi-sensor human action recognition with particular application to tennis event-based indexing

The ability to automatically classify human actions and activities using vi- sual sensors or by analysing body worn sensor data has been an active re- search area for many years. Only recently with advancements in both fields and the ubiquitous nature of low cost sensors in our everyday lives has auto- matic human action recognition become a reality. While traditional sports coaching systems rely on manual indexing of events from a single modality, such as visual or inertial sensors, this thesis investigates the possibility of cap- turing and automatically indexing events from multimodal sensor streams. In this work, we detail a novel approach to infer human actions by fusing multimodal sensors to improve recognition accuracy. State of the art visual action recognition approaches are also investigated. Firstly we apply these action recognition detectors to basic human actions in a non-sporting con- text. We then perform action recognition to infer tennis events in a tennis court instrumented with cameras and inertial sensing infrastructure. The system proposed in this thesis can use either visual or inertial sensors to au- tomatically recognise the main tennis events during play. A complete event retrieval system is also presented to allow coaches to build advanced queries, which existing sports coaching solutions cannot facilitate, without an inordi- nate amount of manual indexing. The event retrieval interface is evaluated against a leading commercial sports coaching tool in terms of both usability and efficiency

Libro de Actas del Primer Congreso Internacional de Análisis de Rendimiento Deportivo y Coaching

Este libro es una compliación de las Comunicaciones y Ponencias presentadas en el I Congreso Internacional de Análisis de Rendimiento Deportivo y Coaching, celebrado en la Facultad de Ciencias de la Actividad Física y el Deporte de la Universidad de Valencia entre el 25 y 27 de Marzo de 2015. Organizado por la Universidad de Valencia y la Asociación Valenciana de Análisis de Rendimiento Deportivo y Coaching.This book is a compilation of Communications and lectures presented at the Firsth International Conference on Performance Analysis and Coaching in Sport, performed in the Faculty of Physical Activity and Sport Sciences of the University of Valencia, 25-27th of March. Organized by the University of Valencia and The Valencian Association of Perfomance Analysis and Coaching in Sport