Indoor Positioning for Monitoring Older Adults at Home: Wi-Fi and BLE Technologies in Real Scenarios

This paper presents our experience on a real case of applying an indoor localization system formonitoringolderadultsintheirownhomes. Sincethesystemisdesignedtobeusedbyrealusers, therearemanysituationsthatcannotbecontrolledbysystemdevelopersandcanbeasourceoferrors. This paper presents some of the problems that arise when real non-expert users use localization systems and discusses some strategies to deal with such situations. Two technologies were tested to provide indoor localization: Wi-Fi and Bluetooth Low Energy. The results shown in the paper suggest that the Bluetooth Low Energy based one is preferable in the proposed task

Efficient AoA-based wireless indoor localization for hospital outpatients using mobile devices

The motivation of this work is to help outpatients find their corresponding departments or clinics, thus, it needs to provide indoor positioning services with a room-level accuracy. Unlike wireless outdoor localization that is dominated by the global positioning system (GPS), wireless indoor localization is still an open issue. Many different schemes are being developed to meet the increasing demand for indoor localization services. In this paper, we investigated the AoA-based wireless indoor localization for outpatients’ wayfinding in a hospital, where Wi-Fi access points (APs) are deployed, in line, on the ceiling. The target position can be determined by a mobile device, like a smartphone, through an efficient geometric calculation with two known APs coordinates and the angles of the incident radios. All possible positions in which the target may appear have been comprehensively investigated, and the corresponding solutions were proven to be the same. Experimental results show that localization error was less than 2.5 m, about 80% of the time, which can satisfy the outpatients’ requirements for wayfinding

A Survey of Positioning Systems Using Visible LED Lights

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe

Indoor positioning system survey using BLE beacons

This project provides a survey of indoor positioning systems and reports experimental work with Bluetooth Low Energy (BLE) Beacons. A positioning algorithm based on the Received Signal Strength Index (RSSI) from Bluetooth Low Energy signals is proposed for indoor tracking of the position of a drone. Experimental tests for characterization of beacon signals are presented. The application of a Kalman filter to reduce the effect of fluctuations in beacons signals is described

Study of evacuation drills through data collection, dimensional analysis, statistical regression, and IoT technologies

Let's imagine the evacuation sirens go off, how soon would we all be out of the building? It will depend how many we are, 1000 people or maybe just 200? It will also depend on the dimensions and design of the building, and above all on how we behave. I mean, the time to assimilate that we have to leave, decide to leave, perhaps delayed by picking something up, waiting for or convincing someone, and other issues that make the exit longer. In other words, it is a system with many components that interact with each other. The foundations of evacuation modeling were established in the 1970s and 80s, these being an analytical breakdown of the total time when carrying out an evacuation taking into account the different issues that could influence each of the defined components. All these aspects were of increasing complexity and began to be studied with the help of computer simulations. Computer simulations are very helpful, but require a large amount of resources to carry them out. They do not avoid the need to carry out evacuation drills and do not allow comparisons between evacuations of different buildings. This Ph.D. thesis proposes a different approach, from a holistic view, of a system as a whole, where each building is a black box characterized by a dimensionless parameter that allows different buildings to be differentiated. The building is the independent variable of the system, while the ratio of evacuation time to people evacuated will be the dependent variable. In this way, the evacuations of different buildings can be compared. One great difficulty concerning the study and research of evacuations is to collect enough data, both quantitative and qualitative. In this Ph.D. thesis, data have been collected from evacuation drills at the University of Valladolid for 10 years. In addition, a new indoor positioning system is proposed to facilitate the collection of future data that could be used to feed both the model proposed by this thesis, and to validate other study models. This Ph.D. thesis offers an unprecedented approach to be able to compare the evacuations of different buildings, taking into account their most relevant characteristics for the evacuation, which until now had not been possible. The theoretical approach is supported by the historical data collected, and by data published by other authors. Furthermore, it also offers a viable solution for collecting more evacuation data using indoor positioning technologies.Imaginemos que suenan las sirenas de evacuación, ¿en cuánto tiempo estaríamos todos fuera del edificio? Dependerá cuantos seamos (¿1.000 personas o quizás sólo 200?), de las dimensiones y diseño del edificio, y sobre todo de cómo nos comportemos, es decir, el tiempo que tardemos en asimilar que tenemos que salir, en decidirnos a salir, quizás en entretenernos en coger algo, o esperar o convencer a alguien, y otras cuestiones que nos pueden entretener. Es decir, se trata de un sistema con multitud de elementos que interaccionan entre sí. Las bases de la modelización de la evacuación se establecieron en las décadas de los años 70 y 80 del siglo XX, siendo un desglose analítico del tiempo total a considerar cuando se efectúa una evacuación teniendo en cuenta las diferentes variables que podían influir en cada uno de los elementos definidos. La modelización de todos estos aspectos de complejidad creciente, pasó a ser estudiado con la ayuda de simulaciones por ordenador. Las simulaciones de ordenador son de gran ayuda pero implican un gran esfuerzo en recursos para poder llevarlas a cabo, no evitan la realización de ejercicios de simulacros y no permiten comparar edificios diferentes. Esta tesis doctoral propone un enfoque diferente, desde una visión holística, como un sistema en su conjunto donde cada edificio sea una caja negra caracterizada con un parámetro adimensional que permita diferenciar edificios distintos, siendo el edificio la variable independiente del sistema mientras que la relación ``tiempo de evacuación entre personas evacuadas'' es la variable dependiente. De esta manera se pueden comparar las evacuaciones de diferentes edificios. Una gran dificultad que tiene el estudio e investigación sobre las evacuaciones es recopilar datos suficientes, tanto cuantitativos como cualitativos, de las mismas. En esta tesis se han recogido los datos de simulacros de evacuación de la Universidad de Valladolid durante 10 años. Además se propone un sistema, basado en localización indoor, para facilitar la recogida de datos futuros, válidos para alimentar tanto al modelo propuesto por esta tesis, como para validar otros modelos de estudio. Esta tesis ofrece un planteamiento novedoso para poder comparar las evacuaciones de edificios diferentes, teniendo en cuenta sus características más relevantes en la evacuación, lo cual, hasta ahora, no había sido posible. El planteamiento teórico se ve respaldado por los datos históricos recogidos y por los datos publicados por otros autores. Además, propone una solución viable para la recopilación de más datos de evacuaciones valiéndose de tecnologías de posicionamiento en interiores.Escuela de DoctoradoDoctorado en Ingeniería Industria

Understanding collaborative workspaces:spatial affordances & time constraints

Abstract. This thesis presents a generic solution for indoor positioning and movement monitoring, positioning data collection and analysis with the aim of improving the interior design of collaborative workspaces. Since the nature of the work and the work attitude of employees varies in different workspaces, no general workspace layout can be applied to all situations. Tailoring workspaces according to the exact needs and requirements of the employees can improve collaboration and productivity. Here, an indoor positioning system based on Bluetooth Low Energy technology was designed and implemented in a pilot area (an IT company), and the position of the employees was monitored during a two months period. The pilot area consisted of an open workplace with workstations for nine employees and two sets of coffee tables, four meeting rooms, two coffee rooms and a soundproof phone booth. Thirteen remixes (BLE signal receivers) provided full coverage over the pilot area, while light durable BLE beacons, which were carried by employees acted as BLE signal broadcasters. The RSSIs of the broadcasted signals from the beacons were recorded by each remix within the range of the signal and the gathered data was stored in a database. The gathered RSSI data was normalized to decrease the effect of workspace obstacles on the signal strength. To predict the position of beacons based on the recorded RSSIs, a few approaches were tested, and the most accurate one was chosen, which provided an above 95% accuracy in predicting the position of each beacon every 3 minutes. This approach was a combination of fingerprinting with a Machine Learning-based Random Forest Classifier. The obtained position results were then used to extract various information about the usage pattern of different workspace areas to accurately access the current layout and the needs of the employees

Augmented reality for emergency situations in buildings with the support of indoor localization

Augmented reality is showing a continuous evolution due to the increasing number of smart glasses that are being used for different applications (e.g. training, marketing, industry, risk avoidance, etc.). In this paper, we present an implementation that uses augmented reality (AR) for emergency situations in smart buildings by means of indoor localization through the use of subGHz beacons. This also includes the mapping of emergency elements in the three-dimensional building, together with some example cases