Gatewatch: um centralizador de dados capturados a partir de pulseiras e relógios inteligentes

TCC(graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Sistemas de Informação.Com o constante crescimento da utilização de dispositivos vestíveis produziu-se um ambiente com falta de padrão na coleta e consumo dos dados originários desses equipamentos, sobretudo pelo fato de que cada dispositivo vem com uma solução própria, fornecida pelas fabricantes. Os relógios e pulseiras são, dentre os dispositivos vestíveis, os mais populares e os mais utilizados, com crescente número de vendas anual por diversas marcas que os produzem. Constantemente seguem um fluxo de troca de dados que passa por enviar dados de smartphones para, em seguida, serem enviados e processados em servidores. Porém essa troca não se apresenta de forma tão acessível já que cada relógio ou pulseira possui um modelo de dados e aplicativos próprios para realizar essas trocas dados. Nesse trabalho desenvolvemos um serviço de captura e armazenamento de dados que independe do dispositivo utilizado, de forma a facilitar o acesso a informação para softwares de empresas. Através de um aplicativo fornecido para o usuário final capturamos essas informações enviando-as para um servidor armazená-las e disponibilizá-las para empresas autorizadas

Design of Recognition and Evaluation System for Table Tennis Players' Motor Skills Based on Artificial Intelligence

With the rapid development of electronic science and technology, the research on wearable devices is constantly updated, but for now, it is not comprehensive for wearable devices to recognize and analyze the movement of specific sports. Based on this, this paper improves wearable devices of table tennis sport, and realizes the pattern recognition and evaluation of table tennis players' motor skills through artificial intelligence. Firstly, a device is designed to collect the movement information of table tennis players and the actual movement data is processed. Secondly, a sliding window is made to divide the collected motion data into a characteristic database of six table tennis benchmark movements. Thirdly, motion features were constructed based on feature engineering, and motor skills were identified for different models after dimensionality reduction. Finally, the hierarchical evaluation system of motor skills is established with the loss functions of different evaluation indexes. The results show that in the recognition of table tennis players' motor skills, the feature-based BP neural network proposed in this paper has higher recognition accuracy and stronger generalization ability than the traditional convolutional neural network.Comment: 34pages, 16figure

Prototype of Notification-Monitoring Wearable

Táto práca sa zaoberá procesom vytvorenia prototypu nositeľného zariadenia, ktoré je schopné merať prejdenú vzdialenost a upozorňovat na notifikácie na jeho zápästí. Upozornenia od všetkých užívateľových aplikácií prichádzajú z užívateľovho smartphonu pomocou Bluetooth Low Energy technológie. Ďalej sa zaoberá zistením užívateľských preferencií o ich aktuálnych hodinkách a iných smart zariadení. Zaujímajú nás aj ich potreby a požiadavky na túto tému. Tieto požiadavky som zosumarizoval a z nich bol vytvorený prototyp pre cieľovú skupinu tohto zariadenia. Boli vytvorené užívateľské požiadavku, low-fidelity prototypy ako nositeľného zariadenia, tak aj aplikácií pre otestovanie a určenie užívateľských priorít na systém. Po naprototypování softwaru bol zvolený hardware na ktorom tento systém má bežať. Bol zvolený SoC (systém na čipe) s CPU a Bluetooth čipom, ktorý podporuje BLE. Pre účely tejto práce bol zvolený čip nRF51822 od Nordic Semiconductor. Po vytvorení modelu základnej dosky a pokuse o osadenie všetkých potrebných komponent bol vytvorený 3D model obalu, ktorý bol vytlačený na 3D tlačiarni. Následne bolo toto riešenie otestované na 2 užívateľoch.This work deals with the process of creating a working prototype of a wearable, which is able to measure walked distance and notifies the user on his wrist. Notifications from all users' applications are coming from users' smartphone via Bluetooth Low Energy. This work focuses on finding out users' preferences about their current watches and other smart wearables, their needs and wants on this topic. I have summarized theses preferences and based on this summarization I have created prototype of an environment (wearable, smartphone application) for target group of users based on this research. I have created user requirements on system, low-fidelity prototypes of mobile application, as well as for wearable, for testing purposes and to assigning priorities on the system. The plan was to create MVP = minimal viable product. After prototyping the software, the hardware was chosen for the wearable, main part of the hardware is the SoC (System on a Chip) with CPU and Bluetooth chip supporting Bluetooth Low Energy. For the purposes of this work nRF51822 from Nordic Semiconductor was chosen. After creating the model of a logic board and assembly attempt, was created 3D model and then the model was 3D printed. The solution was then tested with 2 potentional users