Information privacy is a major concern for consumers adopting emerging technologies dependent on location-based services. This study sought to determine whether a relationship exists among factors of personalization, locatability, perceived playfulness, privacy concern and behavioral intention to disclose personal information for individuals using location-based, geosocial networking applications. Questionnaire responses from undergraduate students at a 4-year university provide insight into these relationships. Multiple regression results indicated that there was a statistically significant relationship between the four significant predictor variables and the dependent variable. Analysis of beta weights, structure coefficients, and commonality analysis shed light on the variance attributable to the predictor variables of the study. Findings provide understanding of the specific factors examined in the study and have implications for consumers, businesses, application designers, and policymakers. The results from this study contribute to an understanding of technology acceptance theory and offer insight into competing beliefs that may affect an individual’s behavioral intention to disclose personal information. Knowledge gained form the study may be useful for overcoming challenges related to consumer adoption of location-based services that require disclosure of personal information.

Ericsson is developing a new technology for accurate indoor positioning, named the HIP-solution. The HIP-solution is a joint product with areas of use in both the public safety market for emergency positioning and as a commercial platform for location based services. The driving force behind the development of Ericsson's HIP solution is E911, a legal requirement imposed in theU.S.where operators are required to position an emergency call within a radius of 50-300 meter, depending on available positioning technology. Location Based Services (LBS) are the other important market for the HIP-solution where the technology can be used to offer customized services for mobile users based on their location, such as guidance to the nearest banking cash machine, or whereabouts of friends or family.   This master thesis is conducted at Ericsson, with the purpose of evaluate the HIP-solutions U.S market potential. The theoretical framework used in this paper is the Real Option Pricing Theory, with emphasis on the Expand Option. The theory provides a context for evaluating the HIP-solutions market potential based not only on its physical characteristics, but also of on future expand options and how well Ericsson manages to capture the cloud of externalities the HIP-solution as a joint product.   Keywords Ericsson, HIP-High Precision In-building Positioning, U.S Emergency positioning legislation, Location Based Serviced, App, Real Option, Expand Option.

Usage of locational data is getting more popular day by day. Location-aware application, context aware application and Ubiquities applications are some of the major categories of applications which are based on locational data. One of the most concerning issues regarding such applications is how to protect user’s privacy against malicious attackers. Failing in this task would result in a total failure for the project, considering how privacy concerns are getting more and more important for the end users. In this project, we will propose a theoretical solution for protecting user privacy in location-based application against inference attacks. Our solution is based on categorizing target users into pre-defined groups (a. k. a. Personas) and utilizing their common characteristics in order to synthesize access control rules for the collected data.

Urban agriculture in post-industrial countries is commonly represented in form of shared community gardens or individual gardening lots. However, within the last years, an increasing number of commercial urban farming enterprises around the globe have started their operations. While recreational projects have received much attention, the commercial and entrepreneurial remained mainly uninvestigated. Using a grounded theory approach, this explorative dissertation aims to contribute to an understanding of farming as a new urban profession and the motivation of commercial urban farmers (CUFs) to grow in the city, rather than the countryside. Based on ten semi-standardized in-depth interviews, this study reveals first, that CUFs merge the commonly rural occupation of farming and their desire for autonomic labor with the urban lifestyle as self-made growers, without significant relevant personal or educational background in farming, using alternative growing techniques. Second, the study finds two CUF categories: urbanists, who perceive themselves as actors in sustainable urban development and pursue urban growing activities to contribute to this target; and bargainers, who regard urban growing as a means to an end to progress to small-scale rural agriculture. This suggests that CUFs must engage in inner negotiations between their economic capabilities, the geographic location, and the more society oriented visions they commit themselves to. This research conceptualizes urban farming as tool to fulfill not only food and sustainability goals, but that could also function as basis for sustainable small-scale growing in the countryside.

The purpose of this study consists of gaining an understanding about Augmented Reality (AR) and if this technology can help land-surveyors to visualize cadastral parcels using an iOS app. In addition, the app is also used to get insights of what it takes for an AR system to replace 2D paper maps completely. In land-surveyors daily work, they usually bring annotated 2D paper maps to locate their assets when they do field work. However, the 2D paper map can be cumbersome to use because the map visualizes assets in 2D while the working environment for land-surveyors is in 3D. Therefore, this study presents an AR app that can visualize cadastral parcels in 3D in collaboration with a company called InfoTrader. This dissertation utilizes a qualitative methodology with a design and creation strategy as well as semi-structured interviews. To get feedback and evaluate the proposed app it was tested with professionals with experience in the land-surveying business. The findings from testing the app indicated that the app could be very useful in different scenarios. Nevertheless, to completely replace the 2D paper map, the AR system should integrate all the layers of information that the 2D map provides.

Tremendous emphasis has been placed on wireless technologies recently and it is expected that mobile communications will become an even bigger key driver for growth and innovation in the near future. The purpose of this paper is to study the securing, development, integration and implementation of an always on, always available, and accessible from anywhere secure wireless communication environment. Our analysis of the different wireless technologies reveals that a number of obstacles have to be managed before truly transparent wireless public data consumer offering is available. Our concern revolves around the technical development and implementation efforts of integrated wireless technologies enveloped with management processes of change and evolution. Wireless technologies have influenced our daily lives and will undoubtedly continue to play a significant role in the future. This dissertation focuses on the interoperation of wireless technologies, exploring, evaluating and presenting representations of secure, fully integrated wireless environments. The purpose is to find a cost effective, open, viable, sustainable consumer orientated high data speed offering which not only adheres to basic security requirements but surpasses it. By bringing the network to the subscriber we generate an “always-on” and “always-available” solution for data requirements fulfilling an ever increasing human demand for access to resources anywhere, anytime. A background literature of various wireless technologies, techniques and value added services is provided. An approach for the securing of critical content over wireless links in chapter seven provides a basis for access by position concepts presented in chapter eight. This secure approach to location-aware mobile access control is an essential security enhancement in the integration and interoperation models illustrated in chapter nine. These models, appropriately named SWARM 1 and SWARM 2 (System for Wireless and Roaming Mobility), illustrate different approaches to achieving a secure, fully coherent, consumer orientated, wireless data communications environment. / Dissertation (MSc (Computer Science))--University of Pretoria, 2003. / Computer Science / unrestricted

Mobile devices have evolved from an accessory to the primary computing device for an increasing portion of the general population. Not only is mobile the primary device, consumers on average have multiple Internet-connected devices. The trend towards mobile has resulted in a shift to “mobile-first” strategies for delivering information and services in business organizations, universities, and government agencies. Though principles for good security design exist, those principles were formulated based upon the traditional workstation configuration instead of the mobile platform. Security design needs to follow the shift to a “mobile-first” emphasis to ensure the usability of the security interface. The mobile platform has constraints on resources that can adversely impact the usability of security. This research sought to identify design principles for usable security for mobile devices that address the constraints of the mobile platform. Security and usability have been seen as mutually exclusive. To accurately identify design principles, the relationship between principles for good security design and usability design must be understood. The constraints for the mobile environment must also be identified, and then evaluated for their impact on the interaction of a consumer with a security interface. To understand how the application of the proposed mobile security design principles is perceived by users, an artifact was built to instantiate the principles. Through a series of guided interactions, the importance of proposed design principles was measured in a simulation, in human-computer interaction, and in user perception. The measures showed a resounding difference between the usability of the same security design delivered on mobile vs. workstation platform. It also reveals that acknowledging the constraints of an environment and compensating for the constraints yields mobile security that is both usable and secure. Finally, the hidden cost of security design choices that distract the user from the surrounding environment were examined from both the security perspective and public safety perspective.

West Dallas AR is an interactive location-based app, using the power of multimedia and augmented reality to highlight the stories shared by West Dallas residents.

With the advances in wireless communication technology and advanced positioning systems, a variety of Location-Based Services (LBS) become available to the public. Mobile users can issue location-based queries to probe their surrounding environments. One important type of query in LBS is moving monitoring queries over mobile objects. Due to the high frequency in location updates and the expensive cost of continuous query processing, server computation capacity and wireless communication bandwidth are the two limiting factors for large-scale deployment of moving object database systems. To address both of the scalability factors, distributed computing has been considered. These schemes enable moving objects to participate as a peer in query processing to substantially reduce the demand on server computation, and wireless communications associated with location updates. In the first part of this dissertation, we propose a distributed framework to process moving monitoring queries over moving objects in a spatial network environment. In the second part of this dissertation, in order to reduce the communication cost, we leverage both on-demand data access and periodic broadcast to design a new hybrid distributed solution for moving monitoring queries in an open space environment. Location-based services make our daily life more convenient. However, to receive the services, one has to reveal his/her location and query information when issuing locationbased queries. This could lead to privacy breach if these personal information are possessed by some untrusted parties. In the third part of this dissertation, we introduce a new privacy protection measure called query l-diversity, and provide two cloaking algorithms to achieve both location kanonymity and query l-diversity to better protect user privacy. In the fourth part of this dissertation, we design a hybrid three-tier architecture to help reduce privacy exposure. In the fifth part of this dissertation, we propose to use Road Network Embedding technique to process privacy protected queries.

No / In this paper we present a new method for accurate real-time facial feature detection. Our method is based on local feature detection and enhancement. Previous work in this area, such as that of Viola and Jones, require looking at the face as a whole. Consequently, such approaches have increased chances of reporting negative hits. Furthermore, such algorithms require greater processing power and hence they are especially not attractive for real-time applications. Through our recent work, we have devised a method to identify the face from real-time images and divide it into regions of interest (ROI). Firstly, based on a face detection algorithm, we identify the face and divide it into four main regions. Then, we undertake a local search within those ROI, looking for specific facial features. This enables us to locate the desired facial features more efficiently and accurately. We have tested our approach using the Cohn-Kanade’s Extended Facial Expression (CK+) database. The results show that applying the ROI has a relatively low false positive rate as well as provides a marked gain in the overall computational efficiency. In particular, we show that our method has a 4-fold increase in accuracy when compared to existing algorithms for facial feature detection.