3,971 research outputs found
Performance Evaluation of Mobile U-Navigation based on GPS/WLAN Hybridization
This paper present our mobile u-navigation system. This approach utilizes
hybridization of wireless local area network and Global Positioning System
internal sensor which to receive signal strength from access point and the same
time retrieve Global Navigation System Satellite signal. This positioning
information will be switched based on type of environment in order to ensure
the ubiquity of positioning system. Finally we present our results to
illustrate the performance of the localization system for an indoor/ outdoor
environment set-up.Comment: Journal of Convergence Information Technology(JCIT
RF Localization in Indoor Environment
In this paper indoor localization system based on the RF power measurements of the Received Signal Strength (RSS) in WLAN environment is presented. Today, the most viable solution for localization is the RSS fingerprinting based approach, where in order to establish a relationship between RSS values and location, different machine learning approaches are used. The advantage of this approach based on WLAN technology is that it does not need new infrastructure (it reuses already and widely deployed equipment), and the RSS measurement is part of the normal operating mode of wireless equipment. We derive the Cramer-Rao Lower Bound (CRLB) of localization accuracy for RSS measurements. In analysis of the bound we give insight in localization performance and deployment issues of a localization system, which could help designing an efficient localization system. To compare different machine learning approaches we developed a localization system based on an artificial neural network, k-nearest neighbors, probabilistic method based on the Gaussian kernel and the histogram method. We tested the developed system in real world WLAN indoor environment, where realistic RSS measurements were collected. Experimental comparison of the results has been investigated and average location estimation error of around 2 meters was obtained
Smart Geographic object: Toward a new understanding of GIS Technology in Ubiquitous Computing
One of the fundamental aspects of ubiquitous computing is the instrumentation
of the real world by smart devices. This instrumentation constitutes an
opportunity to rethink the interactions between human beings and their
environment on the one hand, and between the components of this environment on
the other. In this paper we discuss what this understanding of ubiquitous
computing can bring to geographic science and particularly to GIS technology.
Our main idea is the instrumentation of the geographic environment through the
instrumentation of geographic objects composing it. And then investigate how
this instrumentation can meet the current limitations of GIS technology, and
offers a new stage of rapprochement between the earth and its abstraction. As
result, the current research work proposes a new concept we named Smart
Geographic Object SGO. The latter is a convergence point between the smart
objects and geographic objects, two concepts appertaining respectively to
It's the Human that Matters: Accurate User Orientation Estimation for Mobile Computing Applications
Ubiquity of Internet-connected and sensor-equipped portable devices sparked a
new set of mobile computing applications that leverage the proliferating
sensing capabilities of smart-phones. For many of these applications, accurate
estimation of the user heading, as compared to the phone heading, is of
paramount importance. This is of special importance for many crowd-sensing
applications, where the phone can be carried in arbitrary positions and
orientations relative to the user body. Current state-of-the-art focus mainly
on estimating the phone orientation, require the phone to be placed in a
particular position, require user intervention, and/or do not work accurately
indoors; which limits their ubiquitous usability in different applications. In
this paper we present Humaine, a novel system to reliably and accurately
estimate the user orientation relative to the Earth coordinate system.
Humaine requires no prior-configuration nor user intervention and works
accurately indoors and outdoors for arbitrary cell phone positions and
orientations relative to the user body. The system applies statistical analysis
techniques to the inertial sensors widely available on today's cell phones to
estimate both the phone and user orientation. Implementation of the system on
different Android devices with 170 experiments performed at different indoor
and outdoor testbeds shows that Humaine significantly outperforms the
state-of-the-art in diverse scenarios, achieving a median accuracy of
averaged over a wide variety of phone positions. This is
better than the-state-of-the-art. The accuracy is bounded by the error in the
inertial sensors readings and can be enhanced with more accurate sensors and
sensor fusion.Comment: Accepted for publication in the 11th International Conference on
Mobile and Ubiquitous Systems: Computing, Networking and Services
(Mobiquitous 2014
Authoring and Living Next-Generation Location-Based Experiences
Authoring location-based experiences involving multiple participants,
collaborating or competing in both indoor and outdoor mixed realities, is
extremely complex and bound to serious technical challenges. In this work, we
present the first results of the MAGELLAN European project and how these
greatly simplify this creative process using novel authoring, augmented reality
(AR) and indoor geolocalisation techniques
Localization to Enhance Security and Services in Wi-Fi Networks under Privacy Constraints
Developments of seamless mobile services are faced with two broad challenges, systems security and user privacy - access to wireless systems is highly insecure due to the lack of physical boundaries and, secondly, location based services (LBS) could be used to extract highly sensitive user information. In this paper, we describe our work on developing systems which exploit location information to enhance security and services under privacy constraints. We describe two complimentary methods which we have developed to track node location information within production University Campus Networks comprising of large numbers of users. The location data is used to enhance security and services. Specifically, we describe a method for creating geographic firewalls which allows us to restrict and enhance services to individual users within a specific containment area regardless of physical association. We also report our work on LBS development to provide visualization of spatio-temporal node distribution under privacy considerations
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