Transparent Location Fingerprinting for Wireless Services

Detecting the user location is crucial in a wireless environment, not only for the choice of first-hop communication partners, but also for many auxiliary purposes: Quality of Service (availability of information in the right place for reduced congestion/delay, establishment of the optimal path), energy consumption, automated insertion of location-dependent info into a web query issued by a user (for example a tourist asking informations about a monument or a restaurant, a fireman approaching a disaster area). The technique we propose in our investigation tries to meet two main goals: transparency to the network and independence from the environment. A user entering an environment (for instance a wireless-networked building) shall be able to use his own portable equipment to build a personal map of the environment without the system even noticing it. Preliminary tests allow us to detect position on a map with an average uncertainty of two meters when using information gathered from three IEEE802.11 access points in an indoor environment composed of many rooms on a 625sqm area. Performance is expected to improve when more access points will be exploited in the test area. Implementation of the same techniques on Bluetooth are also being studied

Exploration of location-based services adoption

As mobile technologies become more ubiquitous in the general population, it is reasonable to assume that individuals will consume services and software to enhance their aspirations and entertainment desires. This paper discusses a controlled experiment to explore aspects of user perceptions of their use of location-based services. This study examines a location-based service prototype experiment and analysis based on the UTAUT model. The results show significant indicators that suggest behavior patterns of early adopters of location-based services are being observed. We discuss these influences and attempt to explain their significance. Moreover, more curiously we discuss why some of our model was unsupported and postulate why

Location prediction based on a sector snapshot for location-based services

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shaped cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the new Markov-based mobility prediction (NMMP) and prediction location model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression, and insufficient accuracy. In this paper, a novel cell splitting algorithm is proposed. Also, a new prediction technique is introduced. The cell splitting is universal so it can be applied to all types of cells. Meanwhile, this algorithm is implemented to the Micro cell in parallel with the new prediction technique. The prediction technique, compared with two classic prediction techniques and the experimental results, show the effectiveness and robustness of the new splitting algorithm and prediction technique

Virtual Location-Based Services: Merging the Physical and Virtual World

Location-based services gained much popularity through providing users with helpful information with respect to their current location. The search and recommendation of nearby locations or places, and the navigation to a specific location are some of the most prominent location-based services. As a recent trend, virtual location-based services consider webpages or sites associated with a location as 'virtual locations' that online users can visit in spite of not being physically present at the location. The presence of links between virtual locations and the corresponding physical locations (e.g., geo-location information of a restaurant linked to its website), allows for novel types of services and applications which constitute virtual location-based services (VLBS). The quality and potential benefits of such services largely depends on the existence of websites referring to physical locations. In this paper, we investigate the usefulness of linking virtual and physical locations. For this, we analyze the presence and distribution of virtual locations, i.e., websites referring to places, for two Irish cities. Using simulated tracks based on a user movement model, we investigate how mobile users move through the Web as virtual space. Our results show that virtual locations are omnipresent in urban areas, and that the situation that a user is close to even several such locations at any time is rather the normal case instead of the exception

Privacy through uncertainty in location-based services

Location-Based Services (LBS) are becoming more prevalent. While there are many benefits, there are also real privacy risks. People are unwilling to give up the benefits - but can we reduce privacy risks without giving up on LBS entirely? This paper explores the possibility of introducing uncertainty into location information when using an LBS, so as to reduce privacy risk while maintaining good quality of service. This paper also explores the current uses of uncertainty information in a selection of mobile applications

ADVANCED PERSONALIZATION OF LOCATION BASED SERVICES

This article explores possible solutions for improving Location Based Services (LBS). For the purpose of this paper context, user profile, previous choices and the choice profiles of similar users are aspects taken into consideration. A possible implementation of an LBS system, in the form of a public transport route finding application based on genetic algorithms is also presented. The proposed application uses semantic tagging to integrate data from multiple sources and sensors into a single interpretation.Knowledge Management, Geographic Information Systems, Location-based Services, Semantic Web

Mind your step! : How profiling location reveals your identity - and how you prepare for it

Location-based services (LBS) are services that position your mobile phone to provide some context-based service for you. Some of these services – called ‘location tracking’ applications - need frequent updates of the current position to decide whether a service should be initiated. Thus, internet-based systems will continuously collect and process the location in relationship to a personal context of an identified customer. This paper will present the concept of location as part of a person’s identity. I will conceptualize location in information systems and relate it to concepts like privacy, geographical information systems and surveillance. The talk will present how the knowledge of a person's private life and identity can be enhanced with data mining technologies on location profiles and movement patterns. Finally, some first concepts about protecting location information

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