Leveraging Electromagnetic Polarization in a Two-Antenna Whiteboard in the Air

Wireless sensing, tracking, and drawing technologies are enabling exciting new possibilities for human-machine interaction. They primarily rely on measurements of backscattered phase, amplitude, and Doppler signal distortions, and often require many measurements of these quantities---in time, or from multiple antennas. In this paper we present the design and implementation of PolarDraw, the first whiteboard in the air that sends differentially-polarized wireless signals to glean more precise tracking information from a tag. Leveraging information received from each polarization angle, our novel algorithms infer orientation and position of an RFID-tagged pen using just two antennas, when the user writes in the air or on a physical whiteboard. An experimental comparison in a cluttered indoor office environment compares two-antenna PolarDraw with recent state-of-the-art object tracking systems that use double the number of antennas, demonstrating comparable centimeter-level tracking accuracy and character recognition rates (88--94%), thus making a case for the use of polarization in many other tracking systems

Recognition of activities of daily living

Activities of daily living (ADL) are things we normally do in daily living, including any daily activity such as feeding ourselves, bathing, dressing, grooming, work, homemaking, and leisure. The ability or inability to perform ADLs can be used as a very practical measure of human capability in many types of disorder and disability. Oftentimes in a health care facility, with the help of observations by nurses and self-reporting by residents, professional staff manually collect ADL data and enter data into the system. Technologies in smart homes can provide some solutions to detecting and monitoring a resident’s ADL. Typically multiple sensors can be deployed, such as surveillance cameras in the smart home environment, and contacted sensors affixed to the resident’s body. Note that the traditional technologies incur costly and laborious sensor deployment, and cause uncomfortable feeling of contacted sensors with increased inconvenience. This work presents a novel system facilitated via mobile devices to collect and analyze mobile data pertaining to the human users’ ADL. By employing only one smart phone, this system, named ADL recognition system, significantly reduces set-up costs and saves manpower. It encapsulates rather sophisticated technologies under the hood, such as an agent-based information management platform integrating both the mobile end and the cloud, observer patterns and a time-series based motion analysis mechanism over sensory data. As a single-point deployment system, ADL recognition system provides further benefits that enable the replay of users’ daily ADL routines, in addition to the timely assessment of their life habits

Smart hierarchical WiFi localization system for indoors

Premio Extraordinario de Doctorado de la UAH en el año académico 2013-2014En los últimos años, el número de aplicaciones para smartphones y tablets ha crecido rápidamente. Muchas de estas aplicaciones hacen uso de las capacidades de localización de estos dispositivos. Para poder proporcionar su localización, es necesario identificar la posición del usuario de forma robusta y en tiempo real. Tradicionalmente, esta localización se ha realizado mediante el uso del GPS que proporciona posicionamiento preciso en exteriores. Desafortunadamente, su baja precisión en interiores imposibilita su uso. Para proporcionar localización en interiores se utilizan diferentes tecnologías. Entre ellas, la tecnología WiFi es una de las más usadas debido a sus importantes ventajas tales como la disponibilidad de puntos de acceso WiFi en la mayoría de edificios y que medir la señal WiFi no tiene coste, incluso en redes privadas. Desafortunadamente, también tiene algunas desventajas, ya que en interiores la señal es altamente dependiente de la estructura del edificio por lo que aparecen otros efectos no deseados, como el efecto multicamino o las variaciones de pequeña escala. Además, las redes WiFi están instaladas para maximizar la conectividad sin tener en cuenta su posible uso para localización, por lo que los entornos suelen estar altamente poblados de puntos de acceso, aumentando las interferencias co-canal, que causan variaciones en el nivel de señal recibido. El objetivo de esta tesis es la localización de dispositivos móviles en interiores utilizando como única información el nivel de señal recibido de los puntos de acceso existentes en el entorno. La meta final es desarrollar un sistema de localización WiFi para dispositivos móviles, que pueda ser utilizado en cualquier entorno y por cualquier dispositivo, en tiempo real. Para alcanzar este objetivo, se propone un sistema de localización jerárquico basado en clasificadores borrosos que realizará la localización en entornos descritos topológicamente. Este sistema proporcionará una localización robusta en diferentes escenarios, prestando especial atención a los entornos grandes. Para ello, el sistema diseñado crea una partición jerárquica del entorno usando K-Means. Después, el sistema de localización se entrena utilizando diferentes algoritmos de clasificación supervisada para localizar las nuevas medidas WiFi. Finalmente, se ha diseñado un sistema probabilístico para seguir la posición del dispositivo en movimiento utilizando un filtro Bayesiano. Este sistema se ha probado en un entorno real, con varias plantas, obteniendo un error medio total por debajo de los 3 metros

A Review of pedestrian indoor positioning systems for mass market applications

In the last decade, the interest in Indoor Location Based Services (ILBS) has increased stimulating the development of Indoor Positioning Systems (IPS). In particular, ILBS look for positioning systems that can be applied anywhere in the world for millions of users, that is, there is a need for developing IPS for mass market applications. Those systems must provide accurate position estimations with minimum infrastructure cost and easy scalability to different environments. This survey overviews the current state of the art of IPSs and classifies them in terms of the infrastructure and methodology employed. Finally, each group is reviewed analysing its advantages and disadvantages and its applicability to mass market applications

Doctor of Philosophy

dissertationLow-cost wireless embedded systems can make radio channel measurements for the purposes of radio localization, synchronization, and breathing monitoring. Most of those systems measure the radio channel via the received signal strength indicator (RSSI), which is widely available on inexpensive radio transceivers. However, the use of standard RSSI imposes multiple limitations on the accuracy and reliability of such systems; moreover, higher accuracy is only accessible with very high-cost systems, both in bandwidth and device costs. On the other hand, wireless devices also rely on synchronized notion of time to coordinate tasks (transmit, receive, sleep, etc.), especially in time-based localization systems. Existing solutions use multiple message exchanges to estimate time offset and clock skew, which further increases channel utilization. In this dissertation, the design of the systems that use RSSI for device-free localization, device-based localization, and breathing monitoring applications are evaluated. Next, the design and evaluation of novel wireless embedded systems are introduced to enable more fine-grained radio signal measurements to the application. I design and study the effect of increasing the resolution of RSSI beyond the typical 1 dB step size, which is the current standard, with a couple of example applications: breathing monitoring and gesture recognition. Lastly, the Stitch architecture is then proposed to allow the frequency and time synchronization of multiple nodes' clocks. The prototype platform, Chronos, implements radio frequency synchronization (RFS), which accesses complex baseband samples from a low-power low-cost narrowband radio, estimates the carrier frequency offset, and iteratively drives the difference between two nodes' main local oscillators (LO) to less than 3 parts per billion (ppb). An optimized time synchronization and ranging protocols (EffToF) is designed and implemented to achieve the same timing accuracy as the state-of-the-art but with 59% less utilization of the UWB channel. Based on this dissertation, I could foresee Stitch and RFS further improving the robustness of communications infrastructure to GPS jamming, allow exploration of applications such as distributed beamforming and MIMO, and enable new highly-synchronous wireless sensing and actuation systems

Recent Advances in Indoor Localization Systems and Technologies

Despite the enormous technical progress seen in the past few years, the maturity of indoor localization technologies has not yet reached the level of GNSS solutions. The 23 selected papers in this book present the recent advances and new developments in indoor localization systems and technologies, propose novel or improved methods with increased performance, provide insight into various aspects of quality control, and also introduce some unorthodox positioning methods

Advanced Pedestrian Positioning System to Smartphones and Smartwatches

In recent years, there has been an increasing interest in the development of pedestrian navigation systems for satellite-denied scenarios. The popularization of smartphones and smartwatches is an interesting opportunity for reducing the infrastructure cost of the positioning systems. Nowadays, smartphones include inertial sensors that can be used in pedestrian dead-reckoning (PDR) algorithms for the estimation of the user's position. Both smartphones and smartwatches include WiFi capabilities allowing the computation of the received signal strength (RSS). We develop a new method for the combination of RSS measurements from two different receivers using a Gaussian mixture model. We also analyze the implication of using a WiFi network designed for communication purposes in an indoor positioning system when the designer cannot control the network configuration. In this work, we design a hybrid positioning system that combines inertial measurements, from low-cost inertial sensors embedded in a smartphone, with RSS measurements through an extended Kalman filter. The system has been validated in a real scenario, and results show that our system improves the positioning accuracy of the PDR system thanks to the use of two WiFi receivers. The designed system obtains an accuracy up to 1.4 m in a scenario of 6000 m2