611 resultados para iBeacons iOS app mobile proximity marketing geolocation indoor
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Rapid growth in the global population requires expansion of building stock, which in turn calls for increased energy demand. This demand varies in time and also between different buildings, yet, conventional methods are only able to provide mean energy levels per zone and are unable to capture this inhomogeneity, which is important to conserve energy. An additional challenge is that some of the attempts to conserve energy, through for example lowering of ventilation rates, have been shown to exacerbate another problem, which is unacceptable indoor air quality (IAQ). The rise of sensing technology over the past decade has shown potential to address both these issues simultaneously by providing high–resolution tempo–spatial data to systematically analyse the energy demand and its consumption as well as the impacts of measures taken to control energy consumption on IAQ. However, challenges remain in the development of affordable services for data analysis, deployment of large–scale real–time sensing network and responding through Building Energy Management Systems. This article presents the fundamental drivers behind the rise of sensing technology for the management of energy and IAQ in urban built environments, highlights major challenges for their large–scale deployment and identifies the research gaps that should be closed by future investigations.
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Corporate executives require relevant and intelligent business information in real-time to take strategic decisions. They require the freedom to access this information anywhere and anytime. There is a need to extend this functionality beyond the office and on the fingertips of the decision makers. Mobile Business Intelligence Tool (MBIT) aims to provide these features in a flexible and cost-efficient manner. This paper describes the detailed architecture of MBIT to overcome the limitations of existing mobile business intelligence tools. Further, a detailed implementation framework is presented to realize the design. This research highlights the benefits of using service oriented architecture to design flexible and platform independent mobile business applications. © 2009 IEEE.
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This paper asks a new question: how we can use RFID technology in marketing products in supermarkets and how we can measure its performance or ROI (Return-on-Investment). We try to answer the question by proposing a simulation model whereby customers become aware of other customers' real-time shopping behavior and may hence be influenced by their purchases and the levels of purchases. The proposed model is orthogonal to sales model and can have the similar effects: increase in the overall shopping volume. Managers often struggle with the prediction of ROI on purchasing such a technology, this simulation sets to provide them the answers of questions like the percentage of increase in sales given real-time purchase information to other customers. The simulation is also flexible to incorporate any given model of customers' behavior tailored to particular supermarket, settings, events or promotions. The results, although preliminary, are promising to use RFID technology for marketing products in supermarkets and provide several dimensions to look for influencing customers via feedback, real-time marketing, target advertisement and on-demand promotions. Several other parameters have been discussed including the herd behavior, fake customers, privacy, and optimality of sales-price margin and the ROI of investing in RFID technology for marketing purposes. © 2010 Springer Science+Business Media B.V.
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Customer loyalty can be separated into behavioral loyalty and attitudinal loyalty. This presentation, delivered at the Australian Professional Pharmacists Convention examines ways pharmacists can increase attitudinal long-term customer loyalty.
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Purpose Developments in anti-osteoporosis medications (AOMs) have led to changes in guidelines and policy, which, along with media and marketing strategies, have had an impact upon the prescribing of AOM. The aim was to examine patterns of AOM dispensing in older women (aged 76–81 years at baseline) from 2002 to 2010. Methods Administrative claims data were used to describe AOM dispensing in 4649 participants (born in 1921–1926 and still alive in 2011) in the Australian Longitudinal Study on Women's Health. The patterns were interpreted in the context of changes in guidelines, indications for subsidy, publications (scholarly and general media), and marketing activities. Results Total use of AOM increased from 134 DDD/1000/day in 2002 to 216 DDD/1000/day in 2007 but then decreased to 184 DDD/1000/day in 2010. Alendronate was the most commonly dispensed AOM but decreased from 2007, while use of risedronate (2002 onward), strontium ranelate (2007 onward) and zoledronic acid (2008 onward) increased. Etidronate and hormone replacement therapy (HRT) prescriptions gradually decreased over time. The decline in alendronate dispensing coincided with increases of other bisphosphonates and publicity about potential adverse effects of bisphosphonates, despite relaxing indications for bone density testing and subsidy for AOM. Conclusions Overall dispense of AOM from 2002 reached a peak in 2007 and thereafter declined despite increases in therapeutic options and improved subsidised access. The recent decline in overall AOM dispensing seems to be explained largely by negative publicity rather than specific changes in guidelines and policy.
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Background Diabetic foot ulcers (DFU) are a leading cause of diabetes-related hospitalisation and can be costly to manage without access to appropriate expert care. Within Queensland and indeed across many parts of Australia, there is an inequality in accessing specialist services for individuals with DFU. Recent National Health and Medical Research Council (NHMRC) diabetic foot guidelines recommend remote expert consultation with digital imaging should be made available to people with DFU to improve their clinical outcomes. Telemedicine appears to show promise in improving access to diabetic foot specialist services; however diabetic foot telemedicine models to date have relied upon videoconferencing, store and forward technology and/or customised appliances to obtain digital imagery which all require either expensive infrastructure or a timed reply to the request for advice. Whilst mobile phone advice services have been used with success in general diabetes management and telehealth services have improved diabetic foot outcomes, the rapid emergence in the use of mobile phones has established a need to review the role that various forms of telemedicine play in the management of DFU. The aim of this paper is to review traditional telemedicine modalities that have been used in the management of DFU and to compare that to new and innovative technology that are emerging. Process Studies investigating the management of DFU using various forms of telemedicine interventions will be included in this review. They include the use of videoconferencing technology, hand held digital still photography purpose built imaging devices and mobile phone imagery. Electronic databases (Pubmed, Medline and CINAHL) will be searched using broad MeSH terms and keywords that cover the intended area of interest. Findings It is anticipated that the results of this narrative review will provide delegates of the 2015 Australasian Podiatry Conference an insight into the types of emerging innovative diagnostic telemedicine technologies in the management of DFU against the backdrop of traditional and evidence based modalities. It is anticipated that the findings will drive further research in the area of mobile phone imagery and innovation in the management of DFU.
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Mobile applications are being increasingly deployed on a massive scale in various mobile sensor grid database systems. With limited resources from the mobile devices, how to process the huge number of queries from mobile users with distributed sensor grid databases becomes a critical problem for such mobile systems. While the fundamental semantic cache technique has been investigated for query optimization in sensor grid database systems, the problem is still difficult due to the fact that more realistic multi-dimensional constraints have not been considered in existing methods. To solve the problem, a new semantic cache scheme is presented in this paper for location-dependent data queries in distributed sensor grid database systems. It considers multi-dimensional constraints or factors in a unified cost model architecture, determines the parameters of the cost model in the scheme by using the concept of Nash equilibrium from game theory, and makes semantic cache decisions from the established cost model. The scenarios of three factors of semantic, time and locations are investigated as special cases, which improve existing methods. Experiments are conducted to demonstrate the semantic cache scheme presented in this paper for distributed sensor grid database systems.
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Building on the launch of an early prototype at Balance Unbalance 2013, we now offer a fully realised experience of the ‘Long Time, No See?’ site specific walking/visualisation project for conference users to engage with on a do it yourself basis, either before, during or after the event. ‘Long Time, No See?’ is a new form of participatory, environmental futures project, designed for individuals and groups. It uses a smartphone APP to guide processes of individual or group walking at any chosen location—encouraging walkers to think in radical new ways about how to best prepare for ‘stormy’ environmental futures ahead. As part of their personal journeys participants’ contribute site-specific micro narratives in the form of texts, images and sounds, captured via the APP during the loosely ‘guided’ walk. These responses are then uploaded and synthesised into an ever-building audiovisual and generative artwork/‘map’ of future-thinking affinities, viewable both online at long-time-no-see.org (in Chrome) (and at the same time on a large screen visualisations at QUT’s Cube Centre in Brisbane Australia). The artwork therefore spans both participants’ mobile devices and laptops. If desired outcomes can also be presented publicly in large screen format at the conference. ‘Long Time, No See?’ has been developed over the past two years by a team of leading Australian artists, designers, urban/environmental planners and programmers.
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In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot with-out environment-specific training. Motivated by their ongoing success in various visual recognition tasks, we build our system upon a state-of-the-art convolutional network. We overcome its closed-set limitations by complementing the network with a series of one-vs-all classifiers that can learn to recognize new semantic classes online. Prior domain knowledge is incorporated by embedding the classification system into a Bayesian filter framework that also ensures temporal coherence. We evaluate the classification accuracy of the system on a robot that maps a variety of places on our campus in real-time. We show how semantic information can boost robotic object detection performance and how the semantic map can be used to modulate the robot’s behaviour during navigation tasks. The system is made available to the community as a ROS module.
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This edited volume contains 18 chapters by 40 contributors from many parts the world, and is divided into four thematic sections. The focus of Part 1 is Destination image, and contains five chapters. This has arguably been the most popular topic in the destination marketing literature, underpinned by the knowledge that the image an individual holds of a destination is as important as any tangible features. Yin Chew and Siti Johari attempt to model the relationship between destination image and country image using structural equation modelling. While this does address an important gap in the literature, the measures used to operationalise the constructs are not reported and little of the data analysis is discussed to support the finding that country image is a predictor of destination image. Ana Rodriquez, Antonia Correia and Metin Kozak report the findings of an exploratory study about lakedestination image. They used a neural network content analysis of 40 lake descriptions featuring on an online directory for lake enthusiasts to derive a set of cognitive attribute themes. Yang Zhang and Yi-Wei Xiao explore the relations between literary works and tourism through the Asian voice. Whereas most literary tourism studies have been around Western culture, this is a rare perspective from Chinese culture...
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The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.