WiFiPoz -- an accurate indoor positioning system

Location based services are becoming an important part of life. Wide adoption of GPS in mobile devices combined with cellular networks has practically solved the problem of outdoor localization needs. The problem of locating an indoor user has being studied only recently. Much research contributed to the innovative concept of an indoor positioning system. By analyzing different technologies and algorithms, this thesis concluded that, considering a trade-off between accuracy and cost, a Wi-Fi based Fingerprint method is proved to be the most promising approach to determine the location of a mobile device. However, the Fingerprint method works in two phases-an offline training phase (collection of Received Signal Strength signatures) and an online phase in which data from the first phase is used to determine the current position of a mobile user. The number of training points in a certain area has a direct impact on the accuracy of the system. As a result, the offline phase is a tedious and cumbersome process and the positioning systems are only as accurate as the offline training phase has been detailed. Moreover, the offline phase must be repeated every time a change in the environment occurs. To avoid these limitations, we focus on improving the accuracy of the indoor positioning system, without increasing the number of training points. This thesis presents a Wi-Fi based system for locating a user inside a building. The system is named WiFiPoz, which means Wi-Fi positioning system based on the zoning method. WiFiPoz has a novel approach to Fingerprint method that incorporates Propagation and zoning methods. Experimental results show that WiFiPoz is highly efficient both in accuracy and costs. Compared to traditional Fingerprint methods, with the optimization of the accuracy of the location estimation, WiFiPoz reduces the number of training points. This feature makes it possible to quickly adapt to changes in the environment. In order to explore another possible solution, this thesis also developed, implemented and tested an indoor positioning system named GIS (Geometric Information based positioning System), which is based on a model proposed by another researcher. Several experiments were run in the offline phase and results were compared between the traditional Fingerprint method, GIS and proposed WiFiPoz. We concluded that WiFiPoz is a more efficient and simple way to increase the accuracy of the location determination with fewer training points --Document

New Approach of Indoor and Outdoor Localization Systems

Accurate determination of the mobile position constitutes the basis of many new applications. This book provides a detailed account of wireless systems for positioning, signal processing, radio localization techniques (Time Difference Of Arrival), performances evaluation, and localization applications. The first section is dedicated to Satellite systems for positioning like GPS, GNSS. The second section addresses the localization applications using the wireless sensor networks. Some techniques are introduced for localization systems, especially for indoor positioning, such as Ultra Wide Band (UWB), WIFI. The last section is dedicated to Coupled GPS and other sensors. Some results of simulations, implementation and tests are given to help readers grasp the presented techniques. This is an ideal book for students, PhD students, academics and engineers in the field of Communication, localization & Signal Processing, especially in indoor and outdoor localization domains

A Novel Approach To Intelligent Navigation Of A Mobile Robot In A Dynamic And Cluttered Indoor Environment

The need and rationale for improved solutions to indoor robot navigation is increasingly driven by the influx of domestic and industrial mobile robots into the market. This research has developed and implemented a novel navigation technique for a mobile robot operating in a cluttered and dynamic indoor environment. It divides the indoor navigation problem into three distinct but interrelated parts, namely, localization, mapping and path planning. The localization part has been addressed using dead-reckoning (odometry). A least squares numerical approach has been used to calibrate the odometer parameters to minimize the effect of systematic errors on the performance, and an intermittent resetting technique, which employs RFID tags placed at known locations in the indoor environment in conjunction with door-markers, has been developed and implemented to mitigate the errors remaining after the calibration. A mapping technique that employs a laser measurement sensor as the main exteroceptive sensor has been developed and implemented for building a binary occupancy grid map of the environment. A-r-Star pathfinder, a new path planning algorithm that is capable of high performance both in cluttered and sparse environments, has been developed and implemented. Its properties, challenges, and solutions to those challenges have also been highlighted in this research. An incremental version of the A-r-Star has been developed to handle dynamic environments. Simulation experiments highlighting properties and performance of the individual components have been developed and executed using MATLAB. A prototype world has been built using the WebotsTM robotic prototyping and 3-D simulation software. An integrated version of the system comprising the localization, mapping and path planning techniques has been executed in this prototype workspace to produce validation results

Predictive smart relaying schemes for decentralized wireless systems

Recent developments in decentralized wireless networks make the technology potentially deployable in an extremely broad scenarios and applications. These include mobile Internet of Things (IoT) networks, smart cities, future innovative communication systems with multiple aerial layer flying network platforms and other advanced mobile communication networks. The approach also could be the solution for traditional operated mobile network backup plans, balancing traffic flow, emergency communication systems and so on. This thesis reveals and addresses several issues and challenges in conventional wireless communication systems, particular for the cases where there is a lack of resources and the disconnection of radio links. There are two message routing plans in the data packet store, carry and forwarding form are proposed, known as KaFiR and PaFiR. These employ the Bayesian filtering approach to track and predict the motion of surrounding portable devices and determine the next layer among candidate nodes. The relaying strategies endow smart devices with the intelligent capability to optimize the message routing path and improve the overall network performance with respect to resilience, tolerance and scalability. The simulation and test results present that the KaFiR routing protocol performs well when network subscribers are less mobile and the relaying protocol can be deployed on a wide range of portable terminals as the algorithm is rather simple to operate. The PaFiR routing strategy takes advantages of the Particle Filter algorithm, which can cope with complex network scenarios and applications, particularly when unmanned aerial vehicles are involved as the assisted intermediate layers. When compared with other existing DTN routing protocols and some of the latest relaying plans, both relaying protocols deliver an excellent overall performance for the key wireless communication network evolution metrics, which shows the promising future for this brand new research direction. Further extension work directions based on the tracking and prediction methods are suggested and reviewed. Future work on some new applications and services are also addressed

Restez à l'écoute! un transcodeur automatique de flux RSS

L'utilisation des agrégateurs de news est devenue très commune bien qu'ils requièrent de l'utilisateur qu'il soit devant une écran. Malheureusement, la plupart des gens ne possèdent pas d'écran (ou alors de très petits) lorsqu'ils se déplacent. De plus, cette méthode nécessite des opérations manuelles de l'utilisateur pour accéder aux informations : télécharger un logiciel, décider de générer des fichiers audios à partir des news et envoyer ces fichiers vers, par exemple, un lecteur MP3. Dans ce papier, nous proposons un système qui détecte automatiquement lorsque l'utilisateur quitte la pièce dans laquelle l'ordinateur se situe et envoie directement les news transcodées sur le smartphone de l'utilisateur. Les news agrégées sont donc récupérés par le smartphone de l'utilisateur qui peut dès lors les écouter sans avoir effectué aucune opération manuelle. Nous présentons dans ce papier une telle application, ainsi que les résultats très prometteurs que nous avond déjà obtenus lors de précédents tests

Indoor Positioning and Navigation

In recent years, rapid development in robotics, mobile, and communication technologies has encouraged many studies in the field of localization and navigation in indoor environments. An accurate localization system that can operate in an indoor environment has considerable practical value, because it can be built into autonomous mobile systems or a personal navigation system on a smartphone for guiding people through airports, shopping malls, museums and other public institutions, etc. Such a system would be particularly useful for blind people. Modern smartphones are equipped with numerous sensors (such as inertial sensors, cameras, and barometers) and communication modules (such as WiFi, Bluetooth, NFC, LTE/5G, and UWB capabilities), which enable the implementation of various localization algorithms, namely, visual localization, inertial navigation system, and radio localization. For the mapping of indoor environments and localization of autonomous mobile sysems, LIDAR sensors are also frequently used in addition to smartphone sensors. Visual localization and inertial navigation systems are sensitive to external disturbances; therefore, sensor fusion approaches can be used for the implementation of robust localization algorithms. These have to be optimized in order to be computationally efficient, which is essential for real-time processing and low energy consumption on a smartphone or robot