Analysis of GPS and UWB positioning system for athlete tracking

In recent years, wearable performance monitoring systems have become increasingly popular in competitive sports. Wearable devices can provide vital information including distance covered, velocity, change of direction, and acceleration, which can be used to improve athlete performance and prevent injuries. Tracking technology that monitors the movement of an athlete is an important element of sport wearable devices. For tracking, the cheapest option is to use global positioning system (GPS) data however, their large margins of error are a major concern in many sports. Consequently, indoor positioning systems (IPS) have become popular in sports in recent years where the ultra-wideband (UWB) positioning sensor is now being used for tracking. IPS promises much higher accuracy, but unlike GPS, it requires a longer set-up time and its costs are significantly more. In this research, we investigate the suitability of the UWB-based localisation technique for wearable sports performance monitoring systems. We implemented a hardware set-up for both positioning sensors, UWB and the GPS-based (both 10 Hz and 1 Hz) localisation systems, and then monitored their accuracy in 2D and 3D side-by-side for the sport of tennis. Our gathered data shows a major drawback in the UWB-based localisation system. To address this major drawback we introduce an artificial intelligent model, which shows some promising results

Performance Comparison of TR and FSRUWB System Using Particle Filter: Effects of Frequency, Data Rate, Multi-Path and Multi-Channel Communication

In this study, we introduced a novel scheme based on Transmitted References (TR) and Frequency Shifted Reference (FSR) for ultra-wideband (UWB) system. By taking into account tracking loop-based particle filtering together with a data collecting approach for single and multi-path channel situations, the suggested method is an enhanced model. Each particle's location is determined using this filtering technique, which is then utilised to calculate the timing inaccuracy and regulate the UWB system's timing pulse. Also, it can tackle the multimodal distribution of errors then effectively approximate the optimal solution. The data distribution is discretised via a number of particles that are weighted samples evolving concerning time duration. The simulation results show that, in terms of error rate, number of particles, and delay response, the recommended model of FSR-UWB with particle filter performs better than the TR-UWB with and without considering particle filter

Improving Accuracy in Ultra-Wideband Indoor Position Tracking through Noise Modeling and Augmentation

The goal of this research is to improve the precision in tracking of an ultra-wideband (UWB) based Local Positioning System (LPS). This work is motivated by the approach taken to improve the accuracies in the Global Positioning System (GPS), through noise modeling and augmentation. Since UWB indoor position tracking is accomplished using methods similar to that of the GPS, the same two general approaches can be used to improve accuracy. Trilateration calculations are affected by errors in distance measurements from the set of fixed points to the object of interest. When these errors are systemic, each distinct set of fixed points can be said to exhibit a unique set noise. For UWB indoor position tracking, the set of fixed points is a set of sensors measuring the distance to a tracked tag. In this work we develop a noise model for this sensor set noise, along with a particle filter that uses our set noise model. To the author\u27s knowledge, this noise has not been identified and modeled for an LPS. We test our methods on a commercially available UWB system in a real world setting. From the results we observe approximately 15% improvement in accuracy over raw UWB measurements. The UWB system is an example of an aided sensor since it requires a person to carry a device which continuously broadcasts its identity to determine its location. Therefore the location of each user is uniquely known even when there are multiple users present. However, it suffers from limited precision as compared to some unaided sensors such as a camera which typically are placed line of sight (LOS). An unaided system does not require active participation from people. Therefore it has more difficulty in uniquely identifying the location of each person when there are a large number of people present in the tracking area. Therefore we develop a generalized fusion framework to combine measurements from aided and unaided systems to improve the tracking precision of the aided system and solve data association issues in the unaided system. The framework uses a Kalman filter to fuse measurements from multiple sensors. We test our approach on two unaided sensor systems: Light Detection And Ranging (LADAR) and a camera system. Our study investigates the impact of increasing the number of people in an indoor environment on the accuracies using a proposed fusion framework. From the results we observed that depending on the type of unaided sensor system used for augmentation, the improvement in precision ranged from 6-25% for up to 3 people

Análisis del comportamiento táctico colectivo basado en el dato de posicionamiento en los deportes de equipo: revisión sistemática de las variables tácticas colectivas y valoración de la calidad de la medida

173 p.La tesis doctoral, elaborada en formato clásico, está compuesta por cuatro capítulos: (1) contextualización de la tesis doctoral, (2) objetivos de la tesis doctoral, (3) identificación, análisis de la computación, evaluación crítica y futuras consideraciones de las variables del comportamiento táctico colectivo y de las técnicas de análisis no lineal basado en el dato de posicionamiento en los deportes de equipo y (4) evaluación de la calidad de la medida obtenida mediante la tecnología de radio frecuencia en la medición de las variables de comportamiento táctico colectivo en deportes de equipo: un criterio estándar de calidad.Puesto que la tesis doctoral versará sobre el comportamiento táctico colectivo en los deportes de equipo, el Capítulo 1 analizará los conceptos deporte colectivo y comportamiento táctico colectivo basándose en distintos enfoques. Además, el Capítulo 3 constará de una revisión sistemática que identificará las variables tácticas originales y las técnicas de análisis no lineal empleadas hasta la fecha para analizar el comportamiento táctico colectivo en los deportes de equipo. La tesis doctoral ha considerado el dato de posicionamiento para el análisis del comportamiento táctico colectivo. Puesto que la calidad de la medida es un aspecto fundamental en este proceso, el Capítulo 4 propondrá una herramienta de valoración (i.e., ¿quality criteria standard¿) sobre el proceso de obtención del dato mediante tecnología de radio-frecuencia. De manera complementaria, el último capítulo constará de un estudio preliminar y un estudio de campo con el objetivo de indagar en uno de los criterios considerados en el ¿quality criteria standard¿: el impacto del número de datos insertados por segundo en la medición de las variables tácticas colectivas

Análisis del comportamiento táctico colectivo basado en el dato de posicionamiento en los deportes de equipo: revisión sistemática de las variables tácticas colectivas y valoración de la calidad de la medida

173 p.La tesis doctoral, elaborada en formato clásico, está compuesta por cuatro capítulos: (1) contextualización de la tesis doctoral, (2) objetivos de la tesis doctoral, (3) identificación, análisis de la computación, evaluación crítica y futuras consideraciones de las variables del comportamiento táctico colectivo y de las técnicas de análisis no lineal basado en el dato de posicionamiento en los deportes de equipo y (4) evaluación de la calidad de la medida obtenida mediante la tecnología de radio frecuencia en la medición de las variables de comportamiento táctico colectivo en deportes de equipo: un criterio estándar de calidad.Puesto que la tesis doctoral versará sobre el comportamiento táctico colectivo en los deportes de equipo, el Capítulo 1 analizará los conceptos deporte colectivo y comportamiento táctico colectivo basándose en distintos enfoques. Además, el Capítulo 3 constará de una revisión sistemática que identificará las variables tácticas originales y las técnicas de análisis no lineal empleadas hasta la fecha para analizar el comportamiento táctico colectivo en los deportes de equipo. La tesis doctoral ha considerado el dato de posicionamiento para el análisis del comportamiento táctico colectivo. Puesto que la calidad de la medida es un aspecto fundamental en este proceso, el Capítulo 4 propondrá una herramienta de valoración (i.e., ¿quality criteria standard¿) sobre el proceso de obtención del dato mediante tecnología de radio-frecuencia. De manera complementaria, el último capítulo constará de un estudio preliminar y un estudio de campo con el objetivo de indagar en uno de los criterios considerados en el ¿quality criteria standard¿: el impacto del número de datos insertados por segundo en la medición de las variables tácticas colectivas

Proximity detection protocols for IoT devices

In recent years, we have witnessed the growth of the Internet of Things paradigm, with its increased pervasiveness in our everyday lives. The possible applications are diverse: from a smartwatch able to measure heartbeat and communicate it to the cloud, to the device that triggers an event when we approach an exhibit in a museum. Present in many of these applications is the Proximity Detection task: for instance the heartbeat could be measured only when the wearer is near to a well defined location for medical purposes or the touristic attraction must be triggered only if someone is very close to it. Indeed, the ability of an IoT device to sense the presence of other devices nearby and calculate the distance to them can be considered the cornerstone of various applications, motivating research on this fundamental topic. The energy constraints of the IoT devices are often in contrast with the needs of continuous operations to sense the environment and to achieve high accurate distance measurements from the neighbors, thus making the design of Proximity Detection protocols a challenging task

Motion tracking problems in Internet of Things (IoT) and wireless networking

The dissertation focuses on inferring various motion patterns of internet-of-things (IoT) devices, by leveraging inertial sensors embedded in these objects, as well as wireless signals emitted (or reflected) from them. For instance, we use a combination of GPS signals and inertial sensors on drones to precisely track its 3D orientation over time, ultimately improving safety against failures and crashes. In another application in sports analytics, we embed sensors and radios inside baseballs and cricket balls and compute their 3D trajectory and spin patterns, even when they move at extremely high speeds. In a third application for wireless networks, we explore the possibility of physically moving wireless infrastructure like Access Points and basestations on robots and drones for enhancing the network performance. While these are diverse applications in drones, sports analytics, and wireless networks, the common theme underlying the research is in the development of the core motion-related building blocks. Specifically, we emphasize the philosophy of "fusion of multi modal sensor data with application specific model” as the design principle for building the next generation of diverse IoT applications. To this end, we draw on theoretical techniques in wireless communication, signal processing, and statistics, but translate them to completely functional systems on real-world platforms

Local Positioning Systems in (Game) Sports

Position data of players and athletes are widely used in sports performance analysis for measuring the amounts of physical activities as well as for tactical assessments in game sports. However, positioning sensing systems are applied in sports as tools to gain objective information of sports behavior rather than as components of intelligent spaces (IS). The paper outlines the idea of IS for the sports context with special focus to game sports and how intelligent sports feedback systems can benefit from IS. Henceforth, the most common location sensing techniques used in sports and their practical application are reviewed, as location is among the most important enabling techniques for IS. Furthermore, the article exemplifies the idea of IS in sports on two applications

Ultra Wideband Wearable Sensors for Motion Tracking Applications

The increasing interest and advancements in wearable electronics, biomedical applications and digital signal processing techniques have led to the unceasing progress and research in novel implementations of wireless communications technology. Human motion tracking and localisation are some of the numerous promising applications that have emerged from this interest. Ultra-wideband (UWB) technology is particularly seen as a very attractive solution for microwave-based localisation due to the fine time resolution capabilities of the UWB pulses. However, to prove the viability of utilizing UWB technology for high precision localisation applications, a considerable amount of research work is still needed. The impact of the presence of the human body on localisation accuracy needs to be investigated. In addition, for guaranteeing accurate data retrieval in an impulse-radio based system, the study of pulse distortion becomes indispensable. The objective of the research work presented in this thesis is to study and carry out experimental investigations to formulate new techniques for the development of an Impulse-radio UWB sensor based localisation system for human motion tracking applications. This research work initiates a new approach for human motion tracking by making use of pulsed UWB technology which will allow the development of advanced tracking solutions with the capacity to meet the needs of professional users. Extensive experimental studies involving several ranging and three dimensional localisation investigations have been undertaken, and the potential of achieving high precision localisation using ultra-wideband technology has been demonstrated. Making use of the upper portion of the UWB band, a novel miniature antenna designed for integration in the UWB localisation system is presented and its performance has been examined. The key findings and contributions of this research work include UWB antenna characterisation for pulse based transmission, evaluation of comprehensive antenna fidelity patterns, impact of pulse fidelity on the communication performance of a UWB radio system, along with studies regarding the effect of the human body on received pulse quality and localisation accuracy. In addition, an innovative approach of making use of antenna phase centre information for improving the localisation accuracy has been presented

Artificial Intelligence Of Things For Ubiquitous Sports Analytics

To enable mobile devices to perform in-the-wild sports analytics, particularly swing tracking, remains an open question. A crucial challenge is to develop robust methods that can operate across various sports (e.g., golf and tennis), different sensors (cameras and IMU), and diverse human users. Traditional approaches typically rely on vision-based or IMU-based methods to extract key points from subjects in order to estimate trajectory predictions. However, these methods struggle to generate accurate swing tracking, as vision-based techniques are susceptible to occlusion, and IMU sensors are notorious for accumulated errors. In this thesis, we propose several innovative solutions by leveraging AIoT, including the IoT with ubiquitous wearable devices such as smartphones and smart wristbands, and harnessing the power of AI such as deep neural networks, to achieve ubiquitous sports analytics. We make three main technical contributions: a tailored deep neural network design, network model automatic search, and model domain adaptation to address the problem of heterogeneity among devices, human subjects, and sports for ubiquitous sports analytics. In Chapter 2, we begin with the design of a prototype that combines IMU and depth sensor fusion, along with a tailored deep neural network, to address the occlusion problems faced by depth sensors during swings. To recover swing trajectories with fine-grained details, we propose a CNN-LSTM architecture that learns multi-modalities within depth and IMU sensor fusion. In Chapter 3, we develop a framework to reduce the overhead of model design for new devices, sports, and human users. By designing a regression-based stochastic NAS method, we improve swing-tracking algorithms through automatic model generation. We also extend our studies to include unseen human users, sensor devices, and sports. Leveraging a domain adaptation method, we propose a framework that eliminates the need for tedious training data collection and labeling for new users, devices, and sports via adversarial learning. In Chapter 4, we present a framework to alleviate the model parameter selection process in NAS, as introduced in Chapter 3. By employing zero-cost proxies, we search for the optimal swing tracking architecture without training, in a significantly larger candidate model pool. We demonstrate that the proposed method outperforms state-of-the-art approaches in swing tracking, as well as in adapting to different subjects, sports, and devices. Overall, this thesis develops a series of innovative machine learning algorithms to enable ubiquitous IoT wearable devices to perform accurate swing analytics (e.g., tracking, analysis, and assessment) in real-world conditions