93 resultados para Smart appliance


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The collection documents the history of the Geelong company, Backwell IXL, which commenced in 1858 (first trading under the name E. Backwell & Son) as a blacksmith's shop and stove maker and covers the growth of the business to an appliance, car component and foundry products manufacturer. This collection comprises records, accounts, photographs and product data sheets. It also includes the manuscript of the 'Memoirs of Albert Leslie Backwell', which contained a brief history of the company from the late 1850s to 1980s, including recollections of the management of the company from the early 1920s to the mid 1975s.

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Radio frequency identification (RFID) is a remote identification technique promises to revolutionize the way a specific object use to identify in our industry. However, large scale implementation of RFID sought for protection, against Malware threat, information privacy and un-traceability, for low cost RFID tag. In this paper, we propose a framework to provide privacy for tag data and to provide protection for RFID system from malware. In the proposed framework, malware infected tag is detected by analysing individual component of the RFID tag. It uses sanitization technique for analysing individual component. Here authentication based shared unique parameters is used as a method to protect privacy. This authentication protocol will be capable of handling forward and backward security and identifying rogue reader better than existing protocols. Using this framework, the RFID system will be protected from malware and the privacy of the tag will be ensured as well.

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Surveillance applications in private environments such as smart houses require a privacy management policy if such systems are to be accepted by the occupants of the environment. This is due to the invasive nature of surveillance, and the private nature of the home. In this article, we propose a framework for dynamically altering the privacy policy applied to the monitoring of a smart house based on the situation within the environment. Initially the situation, or context, within the environment is determined; we identify several factors for determining environmental context, and propose methods to quantify the context using audio and binary sensor data. The context is then mapped to an appropriate privacy policy, which is implemented by applying data hiding techniques to control access to data gathered from various information sources. The significance of this work lies in the examination of privacy issues related to assisted-living smart house environments. A single privacy policy in such applications would be either too restrictive for an observer, for example, a carer, or too invasive for the occupants. We address this by proposing a dynamic method, with the aim of decreasing the invasiveness of the technology, while retaining the purpose of the system.

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A smart house can be regarded as a surveillance environment in which the person being observed carries out activities that range from intimate to more public. What can be observed depends on the activity, the person observing (e.g. a carer) and policy. In assisted living smart house environments, a single privacy policy, applied throughout, would be either too invasive for an occupant, or too restrictive for an observer, due to the conflicting goals of surveillance and private environments. Hence, we propose a dynamic method for altering the level of privacy in the environment based on the context, the situation within the environment, encompassing factors relevant to ensuring the occupant's safety and privacy. The context is mapped to an appropriate level of privacy, which is implemented by controlling access to data sources (e.g. video) using data hiding techniques. The aim of this work is to decrease the invasiveness of the technology, while retaining the purpose of the system.

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In this paper we present a framework for addressing privacy issues raised by the monitoring of assisted living smart house environments. In home environments, the conflict between the goals of the surveillance, and the private nature of the home, raises the issue of occupant privacy. This issue needs to be addressed if applications are to be accepted by the occupant. We identify four key properties required for the design of privacy sensitive ubiquitous computing applications. Subsequently, we develop a dynamic and flexible method for implementing privacy measures through controlling access to data, and an interface to provide feedback to the occupant, enabling them to control the implemented privacy measures. We form a generic framework for implementing privacy sensitive ubiquitous computing applications based on previous applications within the field. This framework was then extended and used to develop a specific framework for a privacy sensitive smart house. The approach proposed in the framework dynamically applies privacy measures to multi-modal data according to the situation, or context, of the environment. We further test an implementation of the privacy measures, and detail methods to implement feedback and control. The approach aims to decrease the invasiveness of the surveillance, while retaining the purpose of the assisted living environment.

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Spatial activity recognition is challenging due to the amount of noise incorporated during video tracking in everyday environments. We address the spatial recognition problem with a biologically-inspired chemotactic model that is capable of handling noisy data. The model is based on bacterial chemotaxis, a process that allows bacteria to change motile behaviour in relation to environmental gradients. Through adoption of chemotactic principles, we propose the chemotactic model and evaluate its performance in a smart house environment. The model exhibits greater than 99% recognition performance with a diverse six class dataset and outperforms the Hidden Markov Model (HMM). The approach also maintains high accuracy (90-99%) with small training sets of one to five sequences. Importantly, unlike other low-level spatial activity recognition models, we show that the chemotactic model is capable of recognising simple interwoven activities.

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In this paper, we exploit the discrete Coxian distribution and propose a novel form of stochastic model, termed as the Coxian hidden semi-Makov model (Cox-HSMM), and apply it to the task of recognising activities of daily living (ADLs) in a smart house environment. The use of the Coxian has several advantages over traditional parameterization (e.g. multinomial or continuous distributions) including the low number of free parameters needed, its computational efficiency, and the existing of closed-form solution. To further enrich the model in real-world applications, we also address the problem of handling missing observation for the proposed Cox-HSMM. In the domain of ADLs, we emphasize the importance of the duration information and model it via the Cox-HSMM. Our experimental results have shown the superiority of the Cox-HSMM in all cases when compared with the standard HMM. Our results have further shown that outstanding recognition accuracy can be achieved with relatively low number of phases required in the Coxian, thus making the Cox-HSMM particularly suitable in recognizing ADLs whose movement trajectories are typically very long in nature.

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With the revolution that has taken place in the functionality and uptake of portable networked ‘smart’ technologies, educators are looking to see what potential applications such technologies might have for school education. This article reports on a study into the use of portable personal computing devices in the early years of schooling. Specifically, it focuses on emerging patterns of use of Apple iPads in an Australian Preparatory (first year of compulsory schooling) classroom across the first year of implementation of these devices. We draw on student and teacher interviews and classroom observation data to provide a research meta-narrative of the intentions, practices and reflections of a ‘first year out’ teacher, and to discuss points of tension found in the contested space of early years literacy education, which are highlighted when potentially transformative technologies meet institutionalized literacy education practices. Our findings suggest that the broader policy and curriculum context of early years literacy education, and institutionalized practices found in this space, are potentially at odds with teacher-held intentions to transform learning through technology use, particularly with respect to tensions between print-based traditions and new digital literacies, and those between standards-based classroom curricular and more emancipatory agendas.

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Smart phones are everywhere, people are taking eBook readers on holiday, the iPad has queues of people wanting to buy one, and some netbooks can fit in a pocket. The technology is attractive and increasingly affordable – how can it help an individual in their access to and use of texts, journals, databases, clinical sources, the web and day-to-day information? The Library has been investigating and trialling mobile devices during 2010, and has received interesting feedback from staff and students on the effectiveness of the technology in the University and personal environments. Each device has its strengths and weaknesses depending on the needs of the individual or activity it is supporting – productivity, research, study, clinical or recreational. The presentation will explore these issues along with some of the practical implications at Deakin, and international experiences in academic environments.