Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition

Most wearable activity recognition systems assume a predefined sensor deployment that remains unchanged during runtime. However, this assumption does not reflect real-life conditions. During the normal use of such systems, users may place the sensors in a position different from the predefined sensor placement. Also, sensors may move from their original location to a different one, due to a loose attachment. Activity recognition systems trained on activity patterns characteristic of a given sensor deployment may likely fail due to sensor displacements. In this work, we innovatively explore the effects of sensor displacement induced by both the intentional misplacement of sensors and self-placement by the user. The effects of sensor displacement are analyzed for standard activity recognition techniques, as well as for an alternate robust sensor fusion method proposed in a previous work. While classical recognition models show little tolerance to sensor displacement, the proposed method is proven to have notable capabilities to assimilate the changes introduced in the sensor position due to self-placement and provides considerable improvements for large misplacements.

Testing the performance and feasibility of Bluetooth communications in pervasive systems

Smart and mobile environments require seamless connections. However, due to the frequent process of ''discovery'' and disconnection of mobile devices while data interchange is happening, wireless connections are often interrupted. To minimize this drawback, a protocol that enables an easy and fast synchronization is crucial. Bearing this in mind, Bluetooth technology appears to be a suitable solution to carry on such connections due to the discovery and pairing capabilities it provides. Nonetheless, the time and energy spent when several devices are being discovered and used at the same time still needs to be managed properly. It is essential that this process of discovery takes as little time and energy as possible. In addition to this, it is believed that the performance of the communications is not constant when the transmission speeds and throughput increase, but this has not been proved formally. Therefore, the purpose of this project is twofold: Firstly, to design and build a framework-system capable of performing controlled Bluetooth device discovery, pairing and communications. Secondly, to analyze and test the scalability and performance of the \emph{classic} Bluetooth standard under different scenarios and with various sensors and devices using the framework developed. To achieve the first goal, a generic Bluetooth platform will be used to control the test conditions and to form a ubiquitous wireless system connected to an Android Smartphone. For the latter goal, various stress-tests will be carried on to measure the consumption rate of battery life as well as the quality of the communications between the devices involved.

Influence of Humidity on Fiber Bragg Grating Sensors

We demonstrate the influence of the relative humidity (RH) on the wavelength of fiber Bragg grating sensors (FBGS), performing tests with five FBGS at different humidity and temperature conditions. These tests were performed in a climate chamber whose RH changes according to a scheduled profile from 30% to 90%, in steps of 10%. These profiles were repeated for a wide range of temperatures from to , in steps of . Two different types of instrumentation methods have been tested, spot welding and epoxy bonding, in two different materials, steel and carbon fiber reinforced polymer (CFRP). We discuss the results for each type of sensor and instrumentation method by analyzing the linearity of the Bragg wavelength with RH and temperature.

Estudio de la cinemática de un móvil de dos ruedas y su control para mantener el equilibrio controlado por Bluetooth

Este proyecto se centra en el control de un robot con estabilidad dinámica más concretamente en un robot que responde al conocido modelo del péndulo invertido. Una de las aplicaciones más famosas del péndulo invertido es el Segway. El péndulo invertido del Segway se define solo en un eje, al tener dos ruedas paralelas como soporte. El proyecto general consta de tres partes, poner el robot en equilibrio, el control remoto del robot vía Bluetooth y el uso de los encoders de los motores para manejar el robot. Poner el robot en equilibrio: Esta parte consiste en la lectura e interpretación de los datos que nos ofrece la Unidad de Medición Inercial (IMU) para conseguir que el robot se mantenga horizontalmente en todo momento utilizando un control PID y se ha desarrollado junto al compañero, Anartz Recalde. Las otras dos partes están pensadas con el objetivo de darle más personalidad al proyecto individual de cada uno. Control remoto vía Bluetooth: Con esta parte lo que se pretende es controlar el robot remotamente mediante el Bluetooth y ha sido desarrollada únicamente por mí. Uso de los encoders de los motores para manejar el robot: Esta parte ha sido totalmente desarrollada por Anartz Recalde, y consiste en hacer uso de los encoders de los motores e interpretar los datos que proporcionan para sacar distintos datos como la distancia recorrida o la velocidad. De esta manera, intentará conseguir que el robot en todo momento se mantenga en la misma posición, es decir si alguna fuerza externa al robot hace que el robot se mueva, éste se tiene que situar en la misma posición en la que estaba antes de que se le hubiera ejercido dicha fuerza externa. Por lo tanto, este proyecto consiste en construir un robot balancín, bastante similar a un Segway pero en una escala más pequeña, conseguir que se mantenga en equilibrio y manejarlo por control remoto mediante uso del Bluetooth.

Virtual Sensors for On-line Wheel Wear and Part Roughness Measurement in the Grinding Process

Grinding is an advanced machining process for the manufacturing of valuable complex and accurate parts for high added value sectors such as aerospace, wind generation, etc. Due to the extremely severe conditions inside grinding machines, critical process variables such as part surface finish or grinding wheel wear cannot be easily and cheaply measured on-line. In this paper a virtual sensor for on-line monitoring of those variables is presented. The sensor is based on the modelling ability of Artificial Neural Networks (ANNs) for stochastic and non-linear processes such as grinding; the selected architecture is the Layer-Recurrent neural network. The sensor makes use of the relation between the variables to be measured and power consumption in the wheel spindle, which can be easily measured. A sensor calibration methodology is presented, and the levels of error that can be expected are discussed. Validation of the new sensor is carried out by comparing the sensor's results with actual measurements carried out in an industrial grinding machine. Results show excellent estimation performance for both wheel wear and surface roughness. In the case of wheel wear, the absolute error is within the range of microns (average value 32 mu m). In the case of surface finish, the absolute error is well below R-a 1 mu m (average value 0.32 mu m). The present approach can be easily generalized to other grinding operations.

Influence of Humidity on Fiber Bragg Grating Sensors

We demonstrate the influence of the relative humidity (RH) on the wavelength of fiber Bragg grating sensors (FBGS), performing tests with five FBGS at different humidity and temperature conditions. These tests were performed in a climate chamber whose RH changes according to a scheduled profile from 30% to 90%, in steps of 10%. These profiles were repeated for a wide range of temperatures from 10 degrees C to 70 degrees C, in steps of 10 degrees C. Two different types of instrumentation methods have been tested, spot welding and epoxy bonding, in two different materials, steel and carbon fiber reinforced polymer (CFRP). We discuss the results for each type of sensor and instrumentation method by analyzing the linearity of the Bragg wavelength with RH and temperature.