Performance assessment for mountain bike based on WSN and Cloud Technologies

The mountain bike is one of the most used equipment’s in outdoor sports activities. The thesis describes the design and all development and implementation of Performance Assessment for Mountain Bike based on Wireless Sensor Network (WSN) and Cloud Technologies. The work presents a distributed sensing system for cycling assessment-providing data for objective evaluation of the athlete performance during training. Thus a wireless sensor network attached to the sport equipment provides to the athlete and the coach with performance values during practice. The sensors placed in biker equipment’s behave as nodes of a WSN. This is possible with the developing of IoT-based systems in sports, the tracking and monitoring of athletes in their activities has an important role on his formation as bikers and helps to increase performance, through the analyze of each session. The implemented system performs acquisition, processing and transmission, of data using a ZigBee wireless networks that provide also machine-to-machine communication and data storage in a server located in the cloud. As in many cycling applications use the phone as a module to get the values, this work will be a little different making use of phone/tablet to consult information. The information stored on the cloud server is accessed through a mobile application that analyses and correlates all metrics calculated using the training data obtained during practice. Additional information regarding the health status may be also considered. Therefore, the system permits that athletes perform an unlimited number of trainings that can be accessed at any time through the mobile application by the bikers and coach. Based on capability of the system to save a history of the evolution of each athlete during training the system permits to perform appropriate comparisons between different training sessions and different athlete’s performances.A bicicleta de montanha é um dos equipamentos para desportos no exterior mais usada. A tese descreve todo o desenho, desenvolvimento e implementação de Performance Assessment for Mountain Bike based on WSN and Cloud Technologies. Este apresenta um sistema de deteção distribuída para o aumento do desempenho, melhorar a metodologia da prática do ciclismo e para formação de atletas. Para tal foi desenvolvida e anexada uma rede de sensores que está embutida no equipamento do ciclista, através desta rede de sensores sem fios são obtidos os valores respetivos à interação do utilizador e a sua bicicleta, sendo estes apresentados ao treinador e ao próprio ciclista. Os sensores colocados comportam-se como nós de uma rede de sensores sem fios. Isso é possível com o desenvolvimento de sistemas baseados na Internet das coisas no desporto, a observação da movimentação e monitoramento de atletas nas suas atividades tem um papel importante na sua formação como ciclistas e ajuda a aumentar o desempenho. O sistema é baseado numa rede ZigBee sem fios, que permite a comunicação máquina-para-máquina e o armazenamento de dados num servidor localizado na nuvem. Toda a informação na nuvem pode ser acedida através de uma aplicação mobile que analisa e correlaciona todos os valores calculados usando os dados recolhidos durante o treino efetuado por cada ciclista. Como em muitas aplicações de ciclismo estas usam o telefone como um módulo para obter os valores, neste trabalho o caso é diferente fazendo o uso do telefone/tablet para apenas consultar as informações. Alguma informação sobre o ciclista é fornecida para poder efetuar alguns cálculos, relativos à saúde do ciclista, neste caso toda a energia gasta na prática de um determinado treino. Toda esta informação pode ser acedida através de uma aplicação Android e por consequência num dispositivo Android. Com a aplicação desenvolvida é possível observar e processar toda a informação recolhida através dos sensores implementados, a observação dos dados recolhidos pode ser efetuada pelo treinador responsável, como pelo próprio atleta. Portanto, o sistema permite a realização de um ilimitado número de sessões de treino, estes podem ser consultados a qualquer momento através da aplicação móvel. Fazendo com que seja possível manter um histórico da evolução de cada atleta, podendo assim observar e comparar cada sessão de treino, realizada por cada atleta

Human Digital Twin: A Survey

Digital twin has recently attracted growing attention, leading to intensive research and applications. Along with this, a new research area, dubbed as "human digital twin" (HDT), has emerged. Similar to the conception of digital twin, HDT is referred to as the replica of a physical-world human in the digital world. Nevertheless, HDT is much more complicated and delicate compared to digital twins of any physical systems and processes, due to humans' dynamic and evolutionary nature, including physical, behavioral, social, physiological, psychological, cognitive, and biological dimensions. Studies on HDT are limited, and the research is still in its infancy. In this paper, we first examine the inception, development, and application of the digital twin concept, providing a context within which we formally define and characterize HDT based on the similarities and differences between digital twin and HDT. Then we conduct an extensive literature review on HDT research, analyzing underpinning technologies and establishing typical frameworks in which the core HDT functions or components are organized. Built upon the findings from the above work, we propose a generic architecture for the HDT system and describe the core function blocks and corresponding technologies. Following this, we present the state of the art of HDT technologies and applications in the healthcare, industry, and daily life domain. Finally, we discuss various issues related to the development of HDT and point out the trends and challenges of future HDT research and development

WSN and M2M for mountain biking performance assessment

The thesis describes the design and implementation of the "Smart Mountain Bike” monitoring system enables the acquisition, storage and visualization of data on athlete training referring the cycling activity. The signals provided by the measurement channels are acquired and processed in order to better understand of the variables involved in this sport and consecutively to improve the methodology for the training of athletes. The "Smart Mountain Bike" system consists of a wireless sensor network that acquire data related to the applied force and body position during a training session. Each network end node comprises a microcontroller, a conditioning circuit and a set of sensors. The coordinator node Zig Bee compatible is composed by microcomputer (eg. Raspberry PI or BeagleBone), a GPS and an IMU. The cloud interfacing is done using a 3G/UMTS USB module connected to the microcomputer board. As the main component of the cloud the implemented database is accessed through a mobile application implemented in an Android OS device. The mobile application allows the visualization of the acquired and processed data by the user expressed by the athlete or the coach. This system can be used for other sports and other activities in which it is necessary to monitor physical activities such as physical therapy.Este documento descreve o desenvolvimento de um protótipo "Smart Mountain Bike", este sistema de monitorização permite a recolha, armazenamento e visualização dos dados relativos aos treinos do atleta durante a atividade ciclismo. Esta informação contribui para um melhor entendimento das variáveis envolvidas da prática deste desporto e consecutivamente, melhorar a metodologia de treino dos atletas. O sistema "Smart Mountain Bike" é constituído por uma rede sensores sem fios que recolhe a dados sobre força aplicada e posição do corpo numa sessão de treino, cada nó final da rede é composto por um microcontrolador, um circuito condicionador e um conjunto de sensores. O nó coordenador é composto por um microcomputador, um recetor GPS, um IMU e um módulo de comunicação móvel, este módulo permite um cenário Machine-to-Machine, onde o microcomputador comunica com o a nuvem permitindo o armazenamento da informação recolhida numa base de dados. Esta informação é acedida através de uma aplicação móvel desenvolvida para este projeto, a aplicação móvel permite ao utilizador, atleta ou treinador, visualizar e correlacionar os dados. Este sistema pode ser utilizado noutros desportos e noutras atividades em que seja necessário monitorizar atividades físicas, como por exemplo, fisioterapi

Wearable and BAN Sensors for Physical Rehabilitation and eHealth Architectures

The demographic shift of the population towards an increase in the number of elderly citizens, together with the sedentary lifestyle we are adopting, is reflected in the increasingly debilitated physical health of the population. The resulting physical impairments require rehabilitation therapies which may be assisted by the use of wearable sensors or body area network sensors (BANs). The use of novel technology for medical therapies can also contribute to reducing the costs in healthcare systems and decrease patient overflow in medical centers. Sensors are the primary enablers of any wearable medical device, with a central role in eHealth architectures. The accuracy of the acquired data depends on the sensors; hence, when considering wearable and BAN sensing integration, they must be proven to be accurate and reliable solutions. This book is a collection of works focusing on the current state-of-the-art of BANs and wearable sensing devices for physical rehabilitation of impaired or debilitated citizens. The manuscripts that compose this book report on the advances in the research related to different sensing technologies (optical or electronic) and body area network sensors (BANs), their design and implementation, advanced signal processing techniques, and the application of these technologies in areas such as physical rehabilitation, robotics, medical diagnostics, and therapy

Geometric data understanding : deriving case specific features

There exists a tradition using precise geometric modeling, where uncertainties in data can be considered noise. Another tradition relies on statistical nature of vast quantity of data, where geometric regularity is intrinsic to data and statistical models usually grasp this level only indirectly. This work focuses on point cloud data of natural resources and the silhouette recognition from video input as two real world examples of problems having geometric content which is intangible at the raw data presentation. This content could be discovered and modeled to some degree by such machine learning (ML) approaches like deep learning, but either a direct coverage of geometry in samples or addition of special geometry invariant layer is necessary. Geometric content is central when there is a need for direct observations of spatial variables, or one needs to gain a mapping to a geometrically consistent data representation, where e.g. outliers or noise can be easily discerned. In this thesis we consider transformation of original input data to a geometric feature space in two example problems. The first example is curvature of surfaces, which has met renewed interest since the introduction of ubiquitous point cloud data and the maturation of the discrete differential geometry. Curvature spectra can characterize a spatial sample rather well, and provide useful features for ML purposes. The second example involves projective methods used to video stereo-signal analysis in swimming analytics. The aim is to find meaningful local geometric representations for feature generation, which also facilitate additional analysis based on geometric understanding of the model. The features are associated directly to some geometric quantity, and this makes it easier to express the geometric constraints in a natural way, as shown in the thesis. Also, the visualization and further feature generation is much easier. Third, the approach provides sound baseline methods to more traditional ML approaches, e.g. neural network methods. Fourth, most of the ML methods can utilize the geometric features presented in this work as additional features.Geometriassa käytetään perinteisesti tarkkoja malleja, jolloin datassa esiintyvät epätarkkuudet edustavat melua. Toisessa perinteessä nojataan suuren datamäärän tilastolliseen luonteeseen, jolloin geometrinen säännönmukaisuus on datan sisäsyntyinen ominaisuus, joka hahmotetaan tilastollisilla malleilla ainoastaan epäsuorasti. Tämä työ keskittyy kahteen esimerkkiin: luonnonvaroja kuvaaviin pistepilviin ja videohahmontunnistukseen. Nämä ovat todellisia ongelmia, joissa geometrinen sisältö on tavoittamattomissa raakadatan tasolla. Tämä sisältö voitaisiin jossain määrin löytää ja mallintaa koneoppimisen keinoin, esim. syväoppimisen avulla, mutta joko geometria pitää kattaa suoraan näytteistämällä tai tarvitaan neuronien lisäkerros geometrisia invariansseja varten. Geometrinen sisältö on keskeinen, kun tarvitaan suoraa avaruudellisten suureiden havainnointia, tai kun tarvitaan kuvaus geometrisesti yhtenäiseen dataesitykseen, jossa poikkeavat näytteet tai melu voidaan helposti erottaa. Tässä työssä tarkastellaan datan muuntamista geometriseen piirreavaruuteen kahden esimerkkiohjelman suhteen. Ensimmäinen esimerkki on pintakaarevuus, joka on uudelleen virinneen kiinnostuksen kohde kaikkialle saatavissa olevan datan ja diskreetin geometrian kypsymisen takia. Kaarevuusspektrit voivat luonnehtia avaruudellista kohdetta melko hyvin ja tarjota koneoppimisessa hyödyllisiä piirteitä. Toinen esimerkki koskee projektiivisia menetelmiä käytettäessä stereovideosignaalia uinnin analytiikkaan. Tavoite on löytää merkityksellisiä paikallisen geometrian esityksiä, jotka samalla mahdollistavat muun geometrian ymmärrykseen perustuvan analyysin. Piirteet liittyvät suoraan johonkin geometriseen suureeseen, ja tämä helpottaa luonnollisella tavalla geometristen rajoitteiden käsittelyä, kuten väitöstyössä osoitetaan. Myös visualisointi ja lisäpiirteiden luonti muuttuu helpommaksi. Kolmanneksi, lähestymistapa suo selkeän vertailumenetelmän perinteisemmille koneoppimisen lähestymistavoille, esim. hermoverkkomenetelmille. Neljänneksi, useimmat koneoppimismenetelmät voivat hyödyntää tässä työssä esitettyjä geometrisia piirteitä lisäämällä ne muiden piirteiden joukkoon

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