Signal Attenuation Modelling in WLAN Positioning

Wireless Local Area Networks (WLAN), as the most widely used indoor positioning technology, can localise users by measuring the Received Signal Strength (RSS) from multiple Access Points (AP). The challenges of this approach are that measuring RSS can be easily affected by several parameters, including how the users hold the device, e.g. device orientation, and that accurate maps of RSS are required. This paper (A) introduces a bell-curve model of signal attenuation from orientation, allowing more accurate RSS measurement, and (B) identifies collinearity issues with a path-loss model used to automatically create RSS maps, suggesting a simpler and more robust alternative

How fast can our horses go? Measuring the quality of positioning technologies

Whether Henry Ford or someone else gave us this famous quote, ‘If I had asked people what they wanted, they would have said faster horses’, we may agree that it implies there is a limit to what we can expect from the performance of an existing solution. Science and technology always try to push the boundaries and ‘improve’; improving the quality of our lives or improving the quality of technologies. We, as researchers in the area of navigation, are no exception; we want to improve the quality of navigation services. And there are many ways to do so, and challenges and limitations to those attempts. Some researchers look to improve the accuracy, the reliability, the integrity through different approaches. Some try to reduce or model noise, some try to minimise human error, and some use novel techniques and algorithms for better prediction. Of course, when ‘our horses cannot go any faster’ and there is not much space for improvement for a certain technology or service, researchers may come up with a completely new solution, such as an automobile. Almost all new technologies go through the same exploration period; at the beginning, we want to see how and if it works so we try simple tasks, but then we become more ambitious (or greedier!) and so we introduce it to more difficult challenges until it hits the breaking point. At this point, curious researchers and inventors try to push the boundaries and make the technology better, and if improvement is not possible, they build (invent) a new solution. But what is the ‘quality’ that many of us want to improve? How the quality of a technology or service can be measured in the first place

The usability analysis for the use of augmented reality and visual instructions in navigation services

The use of Augmented Reality and visual cues as a part of navigational instructions, in addition to conventional audio and textual instructions, may improve the experience of the users of the navigation services. This approach can be also more compatible with the way people give instructions in everyday life; People usually associate directions with visual cues (e.g. “turn right at the square”) when giving navigational instructions in their daily conversations. In this regard, landmarks as the unique and easy-to-recognise features can play an important role. Such easy to remember features, which are available both indoors and outdoors, can be helpful when exploring an unfamiliar environment. A Landmark-based navigation service can make users sure that they are on the correct route, as the user is reassured by seeing the landmark whose information/picture has just been provided as a part of navigational instruction. Such advantages of use of landmarks visual information as a part of the instructions can decrease the time of travel and improve the experiences of the users. This paper assesses how landmarks can improve the performance of pedestrian movements following landmark-based navigational instructions

Predictive analytics for enhancing travel time estimation in navigation apps of Apple, Google, and Microsoft

The explosive growth of the location-enabled devices coupled with the increasing use of Internet services has led to an increasing awareness of the importance and usage of geospatial information in many applications. The mobile navigation apps (often called “Maps”), use a variety of available data sources to calculate and predict the travel time for different modes. This paper evaluates the pedestrian mode of Maps apps in three major smartphone operating systems (Android, iOS and Windows Phone). We will demonstrate that the Maps apps on iOS, Android and Windows Phone in pedestrian mode, predict travel time without learning from the individual’s movement profile. Then, we will exemplify that those apps suffer from a specific data quality issue (the absence of information about location and type of pedestrian crossings). Finally, we will illustrate learning from movement profile of individuals using predictive analytics models to improve the accuracy of travel time estimation for each user (personalization)

NoSQL storage and management of geospatial data with emphasis on serving geospatial data using standard geospatial web services

Today a huge amount of geospatial data is being created, collected and used more than ever before. The ever increasing observations and measurements of geo-sensor networks, satellite imageries, point clouds from laser scanning, geospatial data of Location Based Services (LBS) and location-based social networks has become a serious challenge for data management and analysis systems. Traditionally, Relational Database Management Systems (RDBMS) were used to manage and to some extent analyse the geospatial data. Nowadays these systems can be used in many scenarios but there are some situations when using these systems may not provide the required efficiency and effectiveness. In these situations, NoSQL solutions can provide the efficiency necessary for applications using geospatial data. It is important to differentiate between the physical way a NoSQL product is implemented, and the interfaces, coding and access methods they use for the abstraction of data. This paper provides an overview of the major types of NoSQL solutions, their advantages and disadvantages and the challenges they present in managing geospatial data. Then the paper elaborates on serving geospatial data using standard geospatial web services with a NoSQL database as a backend

Indoor location based services market drivers and challenges

Indoor Location Based Service (LBS) applications, such as indoor navigation, have not yet found a prominent position in the market as it deals with many challenges, both technical and non-technical. They include indoor positioning, availability and usability of indoor maps and privacy concerns. If these solved or handled there would be a 10 billion euro market waiting for indoor LBS. There are some upcoming and/or potential solutions and opportunities that may help to handle these challenges. They include new positioning technologies and multi-sensor positioning systems that can be applied for indoors, crowd-source mapping, change in viewpoint regarding the users privacy, standards, regulations and policies that can preserve privacy of LBS users. This paper analyses indoor LBS current markets, the challenges and trends and estimate future growth if theses challenges are handled

Indoor location based services market drivers and challenges

Indoor Location Based Service (LBS) applications, such as indoor navigation, have not yet found a prominent position in the market as it deals with many challenges, both technical and non-technical. They include indoor positioning, availability and usability of indoor maps and privacy concerns. If these solved or handled there would be a 10 billion euro market waiting for indoor LBS. There are some upcoming and/or potential solutions and opportunities that may help to handle these challenges. They include new positioning technologies and multi-sensor positioning systems that can be applied for indoors, crowd-source mapping, change in viewpoint regarding the users privacy, standards, regulations and policies that can preserve privacy of LBS users. This paper analyses indoor LBS current markets, the challenges and trends and estimate future growth if theses challenges are handled

Indoor pedestrian dead reckoning calibration by visual tracking and map information

Currently, Pedestrian Dead Reckoning (PDR) systems are becoming more attractive in market of indoor positioning. This is mainly due to the development of cheap and light Micro Electro-Mechanical Systems (MEMS) on smartphones and less requirement of additional infrastructures in indoor areas. However, it still faces the problem of drift accumulation and needs the support from external positioning systems. Vision-aided inertial navigation, as one possible solution to that problem, has become very popular in indoor localization with satisfied performance than individual PDR system. In the literature however, previous studies use fixed platform and the visual tracking uses feature-extraction-based methods. This paper instead contributes a distributed implementation of positioning system and uses deep learning for visual tracking. Meanwhile, as both inertial navigation and optical system can only provide relative positioning information, this paper contributes a method to integrate digital map with real geographical coordinates to supply absolute location. This hybrid system has been tested on two common operation systems of smartphones as iOS and Android, based on corresponded data collection apps respectively, in order to test the robustness of method. It also uses two different ways for calibration, by time synchronization of positions and heading calibration based on time steps. According to the results, localization information collected from both operation systems has been significantly improved after integrating with visual tracking data

The non-technical challenges of Location Based Services markets: are the users' concerns being ignored?

Location Based Services (LBS) market is growing rapidly, however it has faced several challenges and issues, including the availability of reliable positioning services seamlessly (indoors and outdoors), the privacy protection issues, and the relatively high demands for resources, such as high power consumption and cost. Among all the issues introduced to the markets of LBS, the non-technical issues can be easier to understand for many of ordinary users of LBS and they, consequently, can become yet bigger challenge to the development of LBS markets. Lack of social acceptance of the LBS applications can result in slowing down the growth of the market, if not failure. This paper reviews the non-technical issues of LBS market from users’ perspective and evaluate the significance of their impact on the growth of the market based on the results of a survey conducted and the predictive analysis have been done