A Meta-Review of Indoor Positioning Systems

An accurate and reliable Indoor Positioning System (IPS) applicable to most indoor scenarios has been sought for many years. The number of technologies, techniques, and approaches in general used in IPS proposals is remarkable. Such diversity, coupled with the lack of strict and verifiable evaluations, leads to difficulties for appreciating the true value of most proposals. This paper provides a meta-review that performed a comprehensive compilation of 62 survey papers in the area of indoor positioning. The paper provides the reader with an introduction to IPS and the different technologies, techniques, and some methods commonly employed. The introduction is supported by consensus found in the selected surveys and referenced using them. Thus, the meta-review allows the reader to inspect the IPS current state at a glance and serve as a guide for the reader to easily find further details on each technology used in IPS. The analyses of the meta-review contributed with insights on the abundance and academic significance of published IPS proposals using the criterion of the number of citations. Moreover, 75 works are identified as relevant works in the research topic from a selection of about 4000 works cited in the analyzed surveys

New Cluster Selection and Fine-grained Search for k-Means Clustering and Wi-Fi Fingerprinting

Ponencia presentada en 2020 International Conference on Localization and GNSS (ICL-GNSS), 02-04 June 2020, Tampere, FinlandWi-Fi fingerprinting is a popular technique for Indoor Positioning Systems (IPSs) thanks to its low complexity and the ubiquity of WLAN infrastructures. However, this technique may present scalability issues when the reference dataset (radio map) is very large. To reduce the computational costs, k-Means Clustering has been successfully applied in the past. However, it is a general-purpose algorithm for unsupervised classification. This paper introduces three variants that apply heuristics based on radio propagation knowledge in the coarse and fine-grained searches. Due to the heterogeneity either in the IPS side (including radio map generation) and in the network infrastructure, we used an evaluation framework composed of 16 datasets. In terms of general positioning accuracy and computational costs, the best proposed k-means variant provided better general positioning accuracy and a significantly better computational cost –around 40% lower– than the original k-means

Situation Goodness Method for Weighted Centroid-Based Wi-Fi APs Localization

Knowing the location of Wi-Fi antennas may be critical for indoor localization. However, in a real environment, their positions may be unknown since they can be managed by external entities. This paper introduces a new method for evaluating the suitability of using the weighted centroid method for the 2D localization of a Wi-Fi AP. The method is based on the idea that the weighted centroid method provides its best results when there are fingerprints taken around the AP. In order to find the probability of being in the presence of such situations, a natural neighbor interpolation method is used to find the regions with the highest signal strengths. A geometrical method is then used to characterize that probability based on the distribution of those regions in relation to the AP position estimation given by the weighted centroid method. The paper describes the testing location and the used Wi-Fi fingerprints database. That database is used to create new databases that recreate different sampling possibilities through a samples deletion strategy. The original database and the newly created ones are then used to evaluate the localization results of several AP localization methods and the new method proposed in this paper. The evaluation results have shown that the proposed method is able to provide a proper probability for the suitability of using the weighted centroid method for localizing a Wi-Fi AP

Providing Databases for Different Indoor Positioning Technologies: Pros and Cons of Magnetic Field and Wi-Fi Based Positioning

Localization is one of the main pillars for indoor services. However, it is still very difficult for the mobile sensing community to compare state-of-the-art indoor positioning systems due to the scarcity of publicly available databases. To make fair and meaningful comparisons between indoor positioning systems, they must be evaluated in the same situation, or in the same sets of situations. In this paper, two databases are introduced for studying the performance of magnetic field and Wi-Fi fingerprinting based positioning systems in the same environment (i.e., indoor area). The “magnetic” database contains more than 40,000 discrete captures (270 continuous samples), whereas the “Wi-Fi” one contains 1,140 ones. The environment and both databases are fully detailed in this paper. A set of experiments is also presented where two simple but effective baselines have been developed to test the suitability of the databases. Finally, the pros and cons of both types of positioning techniques are discussed in detail.The authors gratefully acknowledge funding from the European Union through the GEO-C project (H2020-MSCA-ITN- 2014, Grant Agreement no. 642332, http://www.geo-c.eu/). The authors also gratefully acknowledge funding from the Spanish Ministry of Economy and Competitiveness through the “Metodolog´ıas avanzadas para el diseno, desarrollo, eval- ˜ uacion e integraci ´ on de algoritmos de localizaci ´ on en inte- ´ riores” project (Proyectos I+D Excelencia, codigo TIN2015- ´ 70202-P) and the “Red de Posicionamiento y Navegacion en ´ Interiores” network (Redes de Excelencia, codigo TEC2015- ´ 71426-REDT). The authors would like to thank all the current and past members of the Geospatial Technologies Research Group and Ubik Geospatial Solutions S.L. for their valuable help in creating the SmartUJI platform and providing us with the supporting services that allowed integrating the existing GIS services in the applications developed to create both databases

Discovering location based services: A unified approach for heterogeneous indoor localization systems

The technological solutions and communication capabilities offered by the Internet of Things paradigm, in terms of raising availability of wearable devices, the ubiquitous internet connection, and the presence on the market of service-oriented solutions, have allowed a wide proposal of Location Based Services (LBS). In a close future, we foresee that companies and service providers will have developed reliable solutions to address indoor positioning, as basis for useful location based services. These solutions will be different from each other and they will adopt different hardware and processing techniques. This paper describes the proposal of a unified approach for Indoor Localization Systems that enables the cooperation between heterogeneous solutions and their functional modules. To this end, we designed an integrated architecture that, abstracting its main components, allows a seamless interaction among them. Finally, we present a working prototype of such architecture, which is based on the popular Telegram application for Android, as an integration demonstrator. The integration of the three main phases –namely the discovery phase, the User Agent self-configuration, and the indoor map retrieval/rendering– demonstrates the feasibility of the proposed integrated architectur

Evaluating Indoor Positioning Systems in a Shopping Mall: The Lessons Learned From the IPIN 2018 Competition

The Indoor Positioning and Indoor Navigation (IPIN) conference holds an annual competition in which indoor localization systems from different research groups worldwide are evaluated empirically. The objective of this competition is to establish a systematic evaluation methodology with rigorous metrics both for real-time (on-site) and post-processing (off-site) situations, in a realistic environment unfamiliar to the prototype developers. For the IPIN 2018 conference, this competition was held on September 22nd, 2018, in Atlantis, a large shopping mall in Nantes (France). Four competition tracks (two on-site and two off-site) were designed. They consisted of several 1 km routes traversing several floors of the mall. Along these paths, 180 points were topographically surveyed with a 10 cm accuracy, to serve as ground truth landmarks, combining theodolite measurements, differential global navigation satellite system (GNSS) and 3D scanner systems. 34 teams effectively competed. The accuracy score corresponds to the third quartile (75 th percentile) of an error metric that combines the horizontal positioning error and the floor detection. The best results for the on-site tracks showed an accuracy score of 11.70 m (Track 1) and 5.50 m (Track 2), while the best results for the off-site tracks showed an accuracy score of 0.90 m (Track 3) and 1.30 m (Track 4). These results showed that it is possible to obtain high accuracy indoor positioning solutions in large, realistic environments using wearable light-weight sensors without deploying any beacon. This paper describes the organization work of the tracks, analyzes the methodology used to quantify the results, reviews the lessons learned from the competition and discusses its future

The IPIN 2019 Indoor Localisation Competition—Description and Results

IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks

Mis casos clínicos de especialidades odontológicas

Libro que muestra la atención de casos clínicos particulares referente a las diferentes especialidades odontológicasLibro que muestra la atención de casos clínicos particulares referente a las diferentes especialidades odontológicasUniversidad Autónoma de Campeche Universidad Autónoma del Estado de Hidalgo Universidad Autónoma del Estado de Méxic

Agent-based parking occupancy simulation

The existing parking simulations, as most simulations, are intended to gain insights of a system or to make predictions. The knowledge they have provided has built up over the years, and several research works have devised detailed parking system models. This thesis work describes the use of an agent-based parking simulation in the context of a bigger parking system development. It focuses more on flexibility than on fidelity, showing the case where it is relevant for a parking simulation to consume dynamically changing GIS data from external, online sources and how to address this case. The simulation generates the parking occupancy information that sensing technologies should eventually produce and supplies it to the bigger parking system. It is built as a Java application based on the MASON toolkit and consumes GIS data from an ArcGis Server. The application context of the implemented parking simulation is a university campus with free, on-street parking places

Received Signal Strength-based Indoor Positioning: Integrative Outlooks and Solutions

This thesis mainly deals with the stages of model description and evaluation of Indoor Positioning Systems based on fingerprinting. Its first contribution is a meta-review that addresses the current state of the art and provides a critical assessment of the impact of publications on indoor positioning. The second contribution is two open datasets of WiFi and BLE RSS measurements that encourage experimentation and reproducibility of positioning solutions. The third is a set of guides, tools, and methods to improve the collection of WiFi and BLE samples. The fourth contribution is a method of selecting positions to update the characterization of the environment. The fifth contribution is evaluation guides and a procedure to measure the positioning error where the magnitude of the error is the distance of the route that joins the actual position and the estimated position.Esta tesis trata principalmente las etapas de descripción del modelo y evaluación de Sistemas de Posicionamiento en Interiores basados en fingerprinting. Su primera aportación es un meta-review que revisa el estado actual del arte, y brinda una evaluación crítica sobre el impacto de las publicaciones sobre posicionamiento en interiores. La segunda aportación es dos datasets abiertos de mediciones de RSS de WiFi y BLE que fomentan la experimentación y la reproducibilidad de soluciones de posicionamiento. La tercera es un conjunto de guías, herramientas y métodos para mejorar la recolección de muestras de WiFi y BLE. La cuarta aportación es un método de selección de posiciones para actualizar la caracterización del entorno. La quinta aportación son guías de evaluación y un procedimiento para medir el error de posicionamiento donde la magnitud del error es la distancia de la ruta que une la posición real y la posición estimada.Programa de Doctorat en Informàtic