914 resultados para iBeacons iOS app mobile proximity marketing geolocation indoor


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Background Despite considerable effort, most smokers relapse within a few months after quitting due to cigarette craving. The widespread adoption of mobile phones presents new opportunities to provide support during attempts to quit. Objective To design and pilot a mobile app "DistractMe" to enable quitters to access and share distractions and tips to cope with cigarette cravings. Methods A qualitative study with 14 smokers who used DistractMe on their mobiles during the first weeks of their quit attempt. Based on interviews, diaries, and log data, we examined how the app supported quitting strategies. Results Three distinct techniques of coping when using DistractMe were identified: diversion, avoidance, and displacement. We further identified three forms of engagement with tips for coping: preparation, fortification, and confrontation. Overall, strategies to prevent cravings and their effects (avoidance, displacement, preparation, and fortification) were more common than immediate coping strategies (diversion and confrontation). Tips for coping were more commonly used than distractions to cope with cravings, because they helped to fortify the quit attempt and provided opportunities to connect with other users of the application. However, distractions were important to attract new users and to facilitate content sharing. Conclusions Based on the qualitative results, we recommend that mobile phone-based interventions focus on tips shared by peers and frequent content updates. Apps also require testing with larger groups of users to assess whether they can be self-sustaining.

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Mobile dating applications (‘apps’) have increased in popularity over recent years, with Tinder among the first to break into the mainstream heterosexual market. Since mobile dating intensifies the need to confirm that potential dates are not misrepresenting themselves and are safe to meet in person, Tinder’s success indicates that it has allayed these concerns regarding the authenticity of its users. This article combines Giddens’ conceptualization of authenticity, as the ability to reference a coherent biographical narrative, with Callon’s sociology of translation to investigate Tinder’s framing of authenticity within mobile dating. Applying a walkthrough method that interrogates Tinder’s technological architecture, promotional materials, and related media, this hybrid theoretical framework is used to identify how Tinder configures an actor-network that establishes its app as the solution to users’ concerns, enrols individuals in using its features in authenticity claims, and popularizes Tinder’s framing across public discourse. This network of human and non-human actors frames authenticity as being established through one’s Facebook profile and adherence to normative standards relating to age, gender, ethnicity, and socioeconomic status. However, user discourses on other social media identify and challenge negative outcomes of this framing, with normativity fostering discrimination and Facebook verification failing to prevent abusive behavior. This case study of Tinder paves the way for future investigation into user responses to its framing. Further, it demonstrates the efficacy and broader applicability of this theoretical approach for identifying both human and technological influences on the construction of authenticity with digital media.

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This chapter surveys the landscape of mobile dating and hookup apps—understood as media technologies, as businesses, and as sites of social practice. It situates the discussion within the broader contexts of technologically mediated dating and digital sexual cultures. By outlining a number of methodological approaches and data sources that can be used in the study of dating and hookup apps, it equips the reader with tools and approaches for investigating hookup app culture in ways that go beyond “media panics” – the familiar combination of moral panics and media effects which is so prevalent in discussions of sexuality in digital media.

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Modern smart phones often come with a significant amount of computational power and an integrated digital camera making them an ideal platform for intelligents assistants. This work is restricted to retail environments, where users could be provided with for example navigational in- structions to desired products or information about special offers within their close proximity. This kind of applications usually require information about the user's current location in the domain environment, which in our case corresponds to a retail store. We propose a vision based positioning approach that recognizes products the user's mobile phone's camera is currently pointing at. The products are related to locations within the store, which enables us to locate the user by pointing the mobile phone's camera to a group of products. The first step of our method is to extract meaningful features from digital images. We use the Scale- Invariant Feature Transform SIFT algorithm, which extracts features that are highly distinctive in the sense that they can be correctly matched against a large database of features from many images. We collect a comprehensive set of images from all meaningful locations within our domain and extract the SIFT features from each of these images. As the SIFT features are of high dimensionality and thus comparing individual features is infeasible, we apply the Bags of Keypoints method which creates a generic representation, visual category, from all features extracted from images taken from a specific location. A category for an unseen image can be deduced by extracting the corresponding SIFT features and by choosing the category that best fits the extracted features. We have applied the proposed method within a Finnish supermarket. We consider grocery shelves as categories which is a sufficient level of accuracy to help users navigate or to provide useful information about nearby products. We achieve a 40% accuracy which is quite low for commercial applications while significantly outperforming the random guess baseline. Our results suggest that the accuracy of the classification could be increased with a deeper analysis on the domain and by combining existing positioning methods with ours.

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Within the next few pages, I will try to give a wide description of the project that I have been doing for IK4-Ikerlan. For the last six months, I have been working in developing a socket-based application for Apple devices. These devices work under the iOS operative system, which is programmed in Objective-C, a language similar to C. Although I did not have the chance to develop this application for Apple TV, I was able to create an application for iPhone and another one for iPad. The only difference between both applications was the screen resolution, but we decided to make them separately, as it would be really hard to combine both resolutions, and wallpapers, everything in the same workspace. Finally, it is necessary to add that the main goal was not to create a new application for iOS, but to translate an Android application into iOS. To achieve this, it is required to translate Java code into Objective- C, which is the language used to develop applications for all kinds of Apple devices. Fortunately, there is a tool created by Google, which helped us with this exercise. This tool is called j2ObjC, and it is still being developed.

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In a road network, cyclists are the group exposed to the maximum amount of risk. Route choice of a cyclist is often based on level of expertise, perceived or actual road risks, personal decisions, weather conditions and a number of other factors. Consequently, cycling tends to be the only significant travel mode where optimised route choice is not based on least-path or least-time. This paper presents an Android platform based mobile-app for personalised route planning of cyclists in Dublin. The mobile-app, apart from its immediate advantage to the cyclists, acts as the departure point for a number of research projects and aids in establishing some critical calibration values for the cycling network in Dublin. 

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This letter reports the statistical characterization and modeling of the indoor radio channel for a mobile wireless personal area network operating at 868 MHz. Line of sight (LOS) and non-LOS conditions were considered for three environments: anechoic chamber, open office area and hallway. Overall, the Nakagami-m cdf best described fading for bodyworn operation in 60% of all measured channels in anechoic chamber and open office area environments. The Nakagami distribution was also found to provide a good description of Rician distributed channels which predominated in the hallway. Multipath played an important role in channel statistics with the mean recorded m value being reduced from 7.8 in the anechoic chamber to 1.3 in both the open office area and hallway.

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Mutual variation of the received signal which occurs as a consequence of the channel reciprocity property has recently been proposed as a viable method for secret key generation. However, this cannot be strictly maintained in practice as the property is applicable only in the absence of interference. To ensure the propagation defined key remains secret, one requirement is that there remain high degrees of uncertainty between the legitimate users channel response and that of any eavesdropper's. In this paper, we investigate whether such de-correlation occurs for an indoor point-to-point link at 2.45 GHz. This is achieved by computing the localized correlation coefficient between the simultaneous channel response measured by the legitimate users and that of multiple distributed eavesdroppers for static and dynamic scenarios.

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Trabalho de projecto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

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Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

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Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Publicidade e Marketing.

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This project proposes an approach for supporting Indoor Navigation Systems using Pedestrian Dead Reckoning-based methods and by analyzing motion sensor data available in most modern smartphones. Processes suggested in this investigation are able to calculate the distance traveled by a user while he or she is walking. WLAN fingerprint- based navigation systems benefit from the processes followed in this research and results achieved to reduce its workload and improve its positioning estimations.

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Information technologies (ITs), and sports resources and services aid the potential to transform governmental organizations, and play an important role in contributing to sustainable communities development, respectively. Spatial data is a crucial source to support sports planning and management. Low-cost mobile geospatial tools bring productive and accurate data collection, and their use combining a handy and customized graphical user interface (GUI) (forms, mapping, media support) is still in an early stage. Recognizing the benefits — efficiency, effectiveness, proximity to citizens — that Mozambican Minister of Youth and Sports (MJD) can achieve with information resulted from the employment of a low-cost data collection platform, this project presents the development of a mobile mapping application (app) — m-SportGIS — under Open Source (OS) technologies and a customized evolutionary software methodology. The app development embraced the combination of mobile web technologies and Application Programming Interfaces (APIs) (e.g. Sencha Touch (ST), Apache Cordova, OpenLayers) to deploy a native-to-the-device (Android operating system) product, taking advantage of device’s capabilities (e.g. File system, Geolocation, Camera). In addition to an integrated Web Map Service (WMS), was created a local and customized Tile Map Service (TMS) to serve up cached data, regarding the IT infrastructures limitations in several Mozambican regions. m-SportGIS is currently being exploited by Mozambican Government staff to inventory all kind of sports facilities, which resulted and stored data feeds a WebGIS platform to manage Mozambican sports resources.