Indoor location using fingerprinting and fuzzy logic

Indoor location systems cannot rely on technologies such as GPS (Global Positioning System) to determine the position of a mobile terminal, because its signals are blocked by obstacles such as walls, ceilings, roofs, etc. In such environments. The use of alternative techniques, such as the use of wireless networks, should be considered. The location estimation is made by measuring and analysing one of the parameters of the wireless signal, usually the received power. One of the techniques used to estimate the locations using wireless networks is fingerprinting. This technique comprises two phases: in the first phase data is collected from the scenario and stored in a database; the second phase consists in determining the location of the mobile node by comparing the data collected from the wireless transceiver with the data previously stored in the database. In this paper an approach for localisation using fingerprinting based on Fuzzy Logic and pattern searching is presented. The performance of the proposed approach is compared with the performance of classic methods, and it presents an improvement between 10.24% and 49.43%, depending on the mobile node and the Fuzzy Logic parameters.ł

RSS and LEA adaptation for indoor location using fingerprinting

Fingerprinting is an indoor location technique, based on wireless networks, where data stored during the offline phase is compared with data collected by the mobile device during the online phase. In most of the real-life scenarios, the mobile node used throughout the offline phase is different from the mobile nodes that will be used during the online phase. This means that there might be very significant differences between the Received Signal Strength values acquired by the mobile node and the ones stored in the Fingerprinting Map. As a consequence, this difference between RSS values might contribute to increase the location estimation error. One possible solution to minimize these differences is to adapt the RSS values, acquired during the online phase, before sending them to the Location Estimation Algorithm. Also the internal parameters of the Location Estimation Algorithms, for example the weights of the Weighted k-Nearest Neighbour, might need to be tuned for every type of terminal. This paper focuses both approaches, using Direct Search optimization methods to adapt the Received Signal Strength and to tune the Location Estimation Algorithm parameters. As a result it was possible to decrease the location estimation error originally obtained without any calibration procedure.

Indoor location-based analytics systems: Portuguese market compettive assessment and entry procing strategy of BIPs' technology in Sonae Sierra Shopping malls stores

This project attempts to provide an in-depth competitive assessment of the Portuguese indoor location-based analytics market, and to elaborate an entry-pricing strategy for Business Intelligence Positioning System (BIPS) implementation in Portuguese shopping centre stores. The role of industry forces and company’s organizational resources platform to sustain company’s competitive advantage was explored. A customer value-based pricing approach was adopted to assess BIPS value to retailers and maximize Sonae Sierra profitability. The exploratory quantitative research found that there is a market opportunity to explore every store area types with tailored proposals, and to set higher-than-tested membership fees to allow a rapid ROI, concluding there are propitious conditions for Sierra to succeed in BIPS store’s business model in Portugal.

Multi-agent location system in wireless networks

In this paper we propose a flexible Multi-Agent Architecture together with a methodology for indoor location which allows us to locate any mobile station (MS) such as a Laptop, Smartphone, Tablet or a robotic system in an indoor environment using wireless technology. Our technology is complementary to the GPS location finder as it allows us to locate a mobile system in a specific room on a specific floor using the Wi-Fi networks. The idea is that any MS will have an agent known at a Fuzzy Location Software Agent (FLSA) with a minimum capacity processing at its disposal which collects the power received at different Access Points distributed around the floor and establish its location on a plan of the floor of the building. In order to do so it will have to communicate with the Fuzzy Location Manager Software Agent (FLMSA). The FLMSAs are local agents that form part of the management infrastructure of the Wi-Fi network of the Organization. The FLMSA implements a location estimation methodology divided into three phases (measurement, calibration and estimation) for locating mobile stations (MS). Our solution is a fingerprint-based positioning system that overcomes the problem of the relative effect of doors and walls on signal strength and is independent of the network device manufacturer. In the measurement phase, our system collects received signal strength indicator (RSSI) measurements from multiple access points. In the calibration phase, our system uses these measurements in a normalization process to create a radio map, a database of RSS patterns. Unlike traditional radio map-based methods, our methodology normalizes RSS measurements collected at different locations on a floor. In the third phase, we use Fuzzy Controllers to locate an MS on the plan of the floor of a building. Experimental results demonstrate the accuracy of the proposed method. From these results it is clear that the system is highly likely to be able to locate an MS in a room or adjacent room.

A VLC-based beacon location system for mobile applications

This paper proposes a low cost and complexity indoor location and navigation system using visible light communications and a mobile device. LED lamps work as beacons transmitting an identifier code so a mobile device can know its location. Experimental designs for transmitter and receiver interfaces are presented and potential applications are discussed.

Person Localization Using Sensor Information Fusion

Nowadays the incredible grow of mobile devices market led to the need for location-aware applications. However, sometimes person location is difficult to obtain, since most of these devices only have a GPS (Global Positioning System) chip to retrieve location. In order to suppress this limitation and to provide location everywhere (even where a structured environment doesn’t exist) a wearable inertial navigation system is proposed, which is a convenient way to track people in situations where other localization systems fail. The system combines pedestrian dead reckoning with GPS, using widely available, low-cost and low-power hardware components. The system innovation is the information fusion and the use of probabilistic methods to learn persons gait behavior to correct, in real-time, the drift errors given by the sensors.

Localization system for pedestrians based on sensor and information fusion

Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.

Where@UM - Dependable organic radio maps

In the past decade, the research community has been dedicating considerable effort into indoor positioning systems based on Wi-Fi fingerprinting techniques, mainly due to their capability to exploit existing infrastructures. Crowdsourcing approaches, also known as organic, have been proposed recently to address the problem of creating and maintaining the corresponding radio maps. In these organic systems, the users of the system build the radio map themselves while using it to estimate their own position/location. However, most of these collaborative methods, proposed by several authors, assume that all the users are honest and committed to contribute to a good quality radio map. In this paper we assess the quality of a radio map built collaboratively and propose a method to classify the credibility of individual contributions and the reputation of individual users. Experimental results are presented for an organic indoor location system that has been used by more than one hundred users over a period of around 12 months.

Influència del nombre d'usuaris en sistemes de localització en interiors basats en Wi-Fi

El present estudi descriu el procés de creació d'un sistema de localització en interiors que permet investigar les possibles diferències de la precisió de les localitzacions en entorns buits i amb presència d'altres persones. Posteriorment es presenten una sèrie de proves realitzades, s'exposen els seus resultats, així com les conclusions sobre com influencia el nombre d'usuaris a la precisió del sistema.

Map matching by using inertial sensors: literature review

This literature review aims to clarify what is known about map matching by using inertial sensors and what are the requirements for map matching, inertial sensors, placement and possible complementary position technology. The target is to develop a wearable location system that can position itself within a complex construction environment automatically with the aid of an accurate building model. The wearable location system should work on a tablet computer which is running an augmented reality (AR) solution and is capable of track and visualize 3D-CAD models in real environment. The wearable location system is needed to support the system in initialization of the accurate camera pose calculation and automatically finding the right location in the 3D-CAD model. One type of sensor which does seem applicable to people tracking is inertial measurement unit (IMU). The IMU sensors in aerospace applications, based on laser based gyroscopes, are big but provide a very accurate position estimation with a limited drift. Small and light units such as those based on Micro-Electro-Mechanical (MEMS) sensors are becoming very popular, but they have a significant bias and therefore suffer from large drifts and require method for calibration like map matching. The system requires very little fixed infrastructure, the monetary cost is proportional to the number of users, rather than to the coverage area as is the case for traditional absolute indoor location systems.

Development of Software Tools for the Test of Ultra Wide Band Receivers

In the last years, the importance of locating people and objects and communicating with them in real time has become a common occurrence in every day life. Nowadays, the state of the art of location systems for indoor environments has not a dominant technology as instead occurs in location systems for outdoor environments, where GPS is the dominant technology. In fact, each location technology for indoor environments presents a set of features that do not allow their use in the overall application scenarios, but due its characteristics, it can well coexist with other similar technologies, without being dominant and more adopted than the others indoor location systems. In this context, the European project SELECT studies the opportunity of collecting all these different features in an innovative system which can be used in a large number of application scenarios. The goal of this project is to realize a wireless system, where a network of fixed readers able to query one or more tags attached to objects to be located. The SELECT consortium is composed of European institutions and companies, including Datalogic S.p.A. and CNIT, which deal with software and firmware development of the baseband receiving section of the readers, whose function is to acquire and process the information received from generic tagged objects. Since the SELECT project has an highly innovative content, one of the key stages of the system design is represented by the debug phase. This work aims to study and develop tools and techniques that allow to perform the debug phase of the firmware of the baseband receiving section of the readers.

Técnica de localização em ambientes fechados utilizando padrões de redes sem fio.

Localizar objetos ou pessoas no interior de um edifício é de grande interesse. Contudo, diferentemente do que ocorre no exterior de edificações, não há metodologia consagrada para a determinação da posição desses entes nos edifícios. Para o posicionamento em locais abertos existem tecnologias consolidadas, como GNSS (Global Navigation Satellite System), a dificuldade em fazê-lo em interiores é maior. Nesses casos, o GNSS não pode ser utilizado, pois os sinais de rádio dos satélites não conseguem penetrar através das estruturas, enquanto que outras tecnologias são apenas incipientes nesse quesito. Abordagens habituais para a resolução dessa demanda têm se baseado na utilização de propagadores das ondas de rádio do GNSS, no uso da potência de sinais de redes sem fio ou, ainda, no emprego de transmissores infravermelhos. No entanto, uma técnica diferente pode ser empreendida para essa finalidade. Usando-se a assinatura das potências de rádio das redes sem fio nas imediações e no interior da edificação, é possível criar um mapa com base nesses sinais, permitindo a determinação da posição de um objeto. No presente trabalho foram desenvolvidos um sistema para geração do mapa de sinais, com critério de parada e um método de cálculo de posicionamento. Procedeu-se, também, à análise de quatro critérios para o cálculo final da posição do objeto, baseados no uso da distância euclidiana com os conjuntos de roteadores disponíveis. Concluiu-se que, quando o mapa de sinais é pequeno, o posicionamento fracassou. Entretanto, quando a quantidade de sinais geradores do mapa aumenta, os resultados apresentaram melhora significativa, com resultados próximos a 100% de assertividade. Desse modo foi possível determinar uma estimativa boa para o número mínimo de roteadores presentes na base e estabelecer um critério de parada para a fase de criação do mapa de sinais.

Uma plataforma adaptável para localização em ambientes internos

Location systems have become increasingly part of people's lives. For outdoor environments, GPS appears as standard technology, widely disseminated and used. However, people usually spend most of their daily time in indoor environments, such as: hospitals, universities, factories, buildings, etc. In these environments, GPS does not work properly causing an inaccurate positioning. Currently, to perform the location of people or objects in indoor environments no single technology could reproduce for indoors the same result achieved by GPS for outdoors environments. Due to this, it is necessary to consider use of information from multiple sources using diferent technologies. Thus, this work aims to build an Adaptable Platform for Indoor location. Based on this goal, the IndoLoR platform is proposed. This platform aims to allow information reception from diferent sources, data processing, data fusion, data storage and data retrieval for the indoor location context.

Uma plataforma adaptável para localização em ambientes internos

Location systems have become increasingly part of people's lives. For outdoor environments, GPS appears as standard technology, widely disseminated and used. However, people usually spend most of their daily time in indoor environments, such as: hospitals, universities, factories, buildings, etc. In these environments, GPS does not work properly causing an inaccurate positioning. Currently, to perform the location of people or objects in indoor environments no single technology could reproduce for indoors the same result achieved by GPS for outdoors environments. Due to this, it is necessary to consider use of information from multiple sources using diferent technologies. Thus, this work aims to build an Adaptable Platform for Indoor location. Based on this goal, the IndoLoR platform is proposed. This platform aims to allow information reception from diferent sources, data processing, data fusion, data storage and data retrieval for the indoor location context.

Collecting data for indoor mapping of the university of Münster via a location based game

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.