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... discussed in the previous section, it is possible to track the time spent by each player according to the predefmed areas. The statistics acquired in that step is displayed as a table accordingly showing the percentage of time in each part of the field. The crossing of this report with the positioning history allows a heat map report, seen in Fig. 4, showing which parts of the field the player spent more time in. Other reports generated by player are the total distance travelled, number of sprints, maximum speed, ...
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A declarative SQL-like language and a middleware infrastructure are presented for collecting data from different nodes of a pervasive system. Data management is performed by hiding the complexity due to the large underlying heterogeneity of devices, which can span from passive RFID(s) to ad-hoc sensor boards to portable computers. An important feat...
Pervasive computing needs scenarios and applications capable of detecting users, providing them with good-quality contextual information. In this sense we should take full advantage of technologies which make it possible to identify and locate people in a way that is adapted to their requirements.Our aim is to create non-intrusive applications for...
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... But now, this difference decreased to the order of tenths of seconds. Likewise, the physical distance between the players became smaller and smaller in case of many sports making them more and more dynamic [6][7][8]. This accelerated and congested assembly of events require more attention not only from the referees and umpires, but also from the players. ...
In this paper we present a novel system for the tracing of the semicircle line during the play of a basketball game. One of the difficult decisions for a referee in such a game play is to establish if a player traced the semicircle line during a throw to the basket. A wide range of solutions are focused on the image detection techniques which require a lot of expensive cameras and data processors for the run of the classification algorithms. For the moment none of this image analysis technique are 100% accurate. Our system is built around a mesh of ESP8266 system on chip microcontroller. To each ESP8266 block a set of IR proximity sensors are connected and RFID tag reader. All the players are identified by a unique RFID tag code which will identify the player who traced the line. All the data acquired from the sensors is processed by the microcontrollers and saved into the cloud.
... All of the training stages were researched at least once in the field of soccer training research, with one research study [78] related to all the phases of training research. Some of the main researched topics include: injury prediction, prevention and recovery [79][80][81], match analysis [82][83][84], and performed training analysis [85][86][87]. System was developed, and is going to be tested at two soccer clubs. ...
The rapid transformation of our communities and our way of life due to modern technologies has impacted sports as well. Artificial intelligence, computational intelligence, data mining, the Internet of Things (IoT), and machine learning have had a profound effect on the way we do things. These technologies have brought changes to the way we watch, play, compete, and also train sports. What was once simply training is now a combination of smart IoT sensors, cameras, algorithms, and systems just to achieve a new peak: The optimum one. This paper provides a systematic literature review of smart sport training, presenting 109 identified studies. Intelligent data analysis methods are presented, which are currently used in the field of Smart Sport Training (SST). Sport domains in which SST is already used are presented, and phases of training are identified, together with the maturity of SST methods. Finally, future directions of research are proposed in the emerging field of SST.
... Tracking itself is hard, and in other sports it is usually based on inertial sensors such as GPS and RFID tags [35,20,31,36]. For American football, Foina et al. [10] describe a system that analyzes RFID sensor data input to yield player analyses in three stages. But even if they started equipping all players with a sensor in baseball as well, no detailed information about the body motion of a single player during pitch or swing would be gained. ...
The baseball game is often seen as many contests that are performed between individuals. The duel between the pitcher and the batter, for example, is considered the engine that drives the sport. The pitchers use a variety of strategies to gain competitive advantage against the batter, who does his best to figure out the ball trajectory and react in time for a hit. In this work, we propose a system that captures the movements of the pitcher, the batter, and the ball in a high level of detail, and discuss several ways how this information may be processed to compute interesting statistics. We demonstrate on a large database of videos that our methods achieve comparable results as previous systems, while operating solely on video material. In addition, state-of-the-art AI techniques are incorporated to augment the amount of information that is made available for players, coaches, teams, and fans.
... Pendekatan ini mengacu kepada beberapa penelitian tentang pengklasifikasian dengan beberapa pendekatan variabel yang berbeda-beda diantaranya adalah pengolahan citra digital yang dapat digunakan untuk klasifikasi mutu suatu buah dengan membedakan fitur-fitur citra (Prahudaya and Harjoko 2017). Pengenalan pemain dalam suatu olahraga juga dilakukan oleh (Foina et al. 2010) untuk mendeteksi pola pemain yang sedang bertanding. K-NN sendiri merupakan metode untuk melakukan klasifikasi terhadap obyek baru berdasarkan k tetangga terdekat dimana hasil dari query instance yang baru dapat diklasifikasikan berdasar maksimum dari kategori pada k-NN dan kelas yang paling banyak muncul akan menjadi kelas hasil klasifikasi (Zhai et al. 2015). ...
Bulutangkis merupakan salah satu cabang olahraga yang dipertandingkan di ajang olimpiade musim panas. Tercatat pembulutangkis Indonesia telah memperoleh 7 medali emas di ajang tersebut. Hingga saat ini Indonesai belum bisa menambah medali emas satupun dari cabang olahraga lain yang dipertandingkan di Olimpiade. Tak heran bulutangkis menjadi olahraga yang sangat penting di Indonesia. Meskipun bulutangkis bukan berasal dari Indonesia, namun Indonesia telah melahirkan banyak legenda bulutangkis sejak tahun 1960-an hingga sekarang. Di era digital sekarang sport science telah di kembangkan di berbagai negara untuk mendukung kinerja atlit dan official , namun hal ini jika tidak di dukung dengan regenerasi pemain muda, maka estafet prestasi akan menjadi terputus. Betapa pentingnya mempersiapkan pemain muda berpotensi untuk meneruskan tradisi pretasi di cabang bulutangkis. Indonesia merupakan salah satu negara dengan regenerasi pemain muda yang cukup lambat dibanding negara kompetitor yang lain seperti China, Korea Selatan dan Jepang. Implementasi algoritma K-Nearest Neighbor dapat digunakan untuk mengklasifikasikan wilayah dengan potensi atlit bulutangkis tunggal putra di Indonesia sehingga induk organisasi bulutangkis Indonesia lebih muda mendapatkan pemain tunggal putra berpotensi. Dengan menggunakan 1000 data peringkat nasional tunggal putra di Indonesia dan mengkalisifikasikannya menjadi 3 daerah yaitu daerah Berpotensi , cukup berpotensi, dan tidak berpotensi dengan nilai K optimal pada K1 sebesar 70.133
... RFID systems are widely adopted in the sport sector. They are mainly used for implementing timing [19] or athlete tracking [20] systems. However, current applications mostly assign to the RFID tag the task of identifying the athlete, whilst more complex tasks, such as data archive and processing, are delegated to the remote infrastructure. ...
Driven by user demand for new smart systems in the framework of the Internet of Things (IoT) and fueled by technological advances in Radiofrequency Identification (RFID), an increasing number of new IoT-oriented RFID-based devices has appeared in recent years in scientific literature. Some of them conjugate canonical RFID identification with extra functionalities such as sensing, reasoning, memorization, and actuation. In this way, IoT challenging applications can be developed, which distribute processing load till to the extreme nodes of the network, while lying upon the well-established RFID infrastructure. In this work, a reasoned panoramic on the potentialities in the IoT framework of augmented RFID tags is presented and classified. Two applicative scenarios are envisioned, presented and discussed, to illustrate how augmented RFID devices may support advanced IoT systems.
... As GPS is restricted to outdoor use only as well as to good weather conditions, other commonly applied sport approaches for position measuring purposes include the integration of radio-signal such as radiowave based tracking systems (Leser et al., 2011). RFID (Radio-Frequency Identification) is another specific system that is, for example, used for tracking and monitoring players in ball games (Foina et al., 2010). ...
The term pervasive computing or, alternatively, ubiquitous computing describes the current evolution and propagation of information processing in human environment. The main idea behind this development involves the implementation of small, interconnected as well as integrated technologies, objects and activities in human’s everyday life. This “technologization” is meanwhile fully present in various disciplines and fields of activities including sport and sport science (Baca et al., 2009). Pervasive computing in sport is a research area of the interdisciplinary field of computer science in sport that has a high impact on the current development of sport (Link & Lames, 2009).
... The system can project targets for players to hit and act as coaching program as player's performance improves. A. G. Foina et [1][10] al have designed a tool to help sports coaches to analyze their players using an RFID technology connected to 3-layer software. The system has two tracking modes, one for 2D player location in the field and a 3D mode to capture player's movement in small area sports. ...
The technology in the present world is an edge cutting in nature. The transformation of the technology is at various dimensions. Computing the data and the process of data and its interpretation is changing around the time in nature at its occupancy in the world. Computation of the data is transforming to a greater extent from the Grid to Cloud computing at high speed. The technology available today is not only a data processing one it has various dimensions and applications at which the performance of the these software's are achieving a higher accuracy and greater results. These technologies can also be implemented in sports which are a modern war fields. Games such as Football, Rugby, Hockey, and Cricket, Tennis and many other Team and single player games are being considered as prestige to their countries. The Judges or the umpires in those games have a great deal and value for their decision and sometimes their fault would turn the nature of the game. This research work is purely focused on the automated decision making in sports purely levering Ubiquitous Computing. Cricket is primarily a popular game in the eastern countries and now a more popular one after football is chosen for implementing this idea of automated decision making. The main objective of this paper is to achieve certain goals 1) Make a decision where a human error makes errors due to limitations. 2) Simulate the Match activity during and after the game in a 3D computerized Graphics system. 3) Make various types of game and performance analysis of a certain team or a player.
... A. G. Foina et al [8] have designed a tool to help sports coaches to analyze their players using an RFID technology connected to 3-layer software. The system has two tracking modes, one for 2D player location in the field and a 3 D mode to capture player's movement in small area sports. ...
The most profound technologies are those that disappear. They weave
themselves into fabrics of everyday life until they are indistinguishable from
it [1]. This research work is a mere effort for automated decision making
during sports of most common interest leveraging ubiquitous computing.
Primarily cricket has been selected for the first implementation of the idea. A
positioning system is used for locating the objects moving in the field. Main
objectives of the research are to help achieve the following goals. 1) Make
Decisions where human eye can make error due to human limitations. 2) Simulate
the Match activity during and after the game in a 3D computerized Graphics
system. 3) Make various types of game and performance analysis of a certain
team or a player.
In team sport Human Activity Recognition (HAR) using inertial measurement units (IMUs) has been limited to athletes performing a set routine in a controlled environment, or identifying a high intensity event within periods of relatively low work load. The purpose of this study was to automatically classify locomotion in an elite sports match where subjects perform rapid changes in movement type, direction, and intensity. Using netball as a test case, six athletes wore a tri-axial accelerometer and gyroscope. Feature extraction of player acceleration and rotation rates was conducted on the time and frequency domain over a 1s sliding window. Applying several machine learning algorithms Support Vector Machines (SVM) was found to have the highest classification accuracy (92.0%, Cohen’s kappa Ƙ = 0.88). Highest accuracy was achieved using both accelerometer and gyroscope features mapped to the time and frequency domain. Time and frequency domain data sets achieved identical classification accuracy (91%). Model accuracy was greatest when excluding windows with two or more classes, however detecting the athlete transitioning between locomotion classes was successful (69%). The proposed method demonstrated HAR of locomotion is possible in elite sport, and a far more efficient process than traditional video coding methods.
