12 resultados para iBeacon Localizzazione Indoor BluetoothLE Prossimità Microgeolocalizzazione

em Deakin Research Online - Australia


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This paper investigates two independent approaches to verify the necessary and sufficient condition to guarantee a unique solution for a passive emitter localization system based on time difference of arrival measurements from an
array of sensors.

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In 2006-7 the Australian government will invest $9.3 billion in state government and nongovernment educational facilities (DEST 20061). One area of particular interest to both government and school designers is maximising this investment through providing students with healthy and
productive indoor learning environments. The lack of post-occupancy evaluations carried out in schools (Lackney 2001) means that designers are reliant on “best practice” indoor environment quality guidelines developed primarily from scientific studies. The problem with scientific evaluation is that often the complexity of the influences upon student performance is simplified in order to gather information, rather than necessarily providing a more holistic and realistic explanation of any improved outcomes. This paper examines the scope of various studies of classroom indoor environment qualities that have thus far contributed to current understanding of their impact on student learning outcomes. The review demonstrates the lack of comprehensive research into the full range of influences on student performance and offers a better understanding of the limitations of knowledge about indoor environment qualities. This information provides valuable input to research development and post-occupancy evaluation that can better integrate the full range of influences upon students of school facilities and test the assumptions made about “best practice”.

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This paper presents a summary of the results from a post-occupancy evaluation study on indoor environment quality (lEO) and occupant health, wellbeing and productivity in the Council House 2 (CH2) building, which is owned and occupied by the City of Melbourne. This case study has highlighted that the productivity of office building occupants can potentially be enhanced through good building design, and provision of a high quality, healthy, comfortable and functional interior environment, that takes account of basic occupant needs.

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Traditional methods of object recognition are reliant on shape and so are very difficult to apply in cluttered, wideangle and low-detail views such as surveillance scenes. To address this, a method of indirect object recognition is proposed, where human activity is used to infer both the location and identity of objects. No shape analysis is necessary. The concept is dubbed 'interaction signatures', since the premise is that a human will interact with objects in ways characteristic of the function of that object - for example, a person sits in a chair and drinks from a cup. The human-centred approach means that recognition is possible in low-detail views and is largely invariant to the shape of objects within the same functional class. This paper implements a Bayesian network for classifying region patches with object labels, building upon our previous work in automatically segmenting and recognising a human's interactions with the objects. Experiments show that interaction signatures can successfully find and label objects in low-detail views and are equally effective at recognising test objects that differ markedly in appearance from the training objects.

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This paper presents a framework for indoor location prediction system using multiple wireless signals available freely in public or office spaces. We first propose an abstract architectural design for the system, outlining its key components and their functionalities. Different from existing works, such as robot indoor localization which requires as precise localization as possible, our work focuses on a higher grain: location prediction. Such a problem has a great implication in context-aware systems such as indoor navigation or smart self-managed mobile devices (e.g., battery management). Central to these systems is an effective method to perform location prediction under different constraints such as dealing with multiple wireless sources, effects of human body heats or mobility of the users. To this end, the second part of this pa- per presents a comparative and comprehensive study on different choices for modeling signals strengths and prediction methods under different condition settings. The results show that with simple, but effective modeling method, almost perfect prediction accuracy can be achieved in the static environment, and up to 85% in the presence of human movements. Finally, adopting the proposed framework we outline a fully developed system, named Marauder, that support user interface interaction and real-time voice-enabled location prediction.

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Aquatic centres are popular recreational facilities in Australia and other developed countries. These buildings have experienced exponential demand over the past few decades. The growing desire for better indoor environmental quality in aquatic centres has resulted in a marked increase in energy consumption in this sector. With the existence of multiple user groups, achieving thermal comfort has always been challenging. Even though several thermal comfort studies are conducted in other building types, such studies are very limited with respect to aquatic centres. This paper analyses the thermal comfort conditions of various user groups in seven aquatic centres in Australia. Comfort measurements are performed through monitoring environmental parameters and surveying swimmers, staff and spectators. The results revealed the variation of air temperatures among the buildings, resulting in high level of thermal discomfort for the spectators and staff in some of the buildings. The thermal sensation of the staff and spectators had good correlation with the indoor temperatures and PMVs. Altering temperature settings according to the seasons will help to improve the comfort with respect to the adaptation and expectation of the occupants.

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Aquatic centres are popular recreational facilities in Australia and other developed countries. These buildings have experienced exponential demand over the past few decades. The growing desire for better indoor environmental quality in aquatic centres has resulted in a marked increase in energy consumption in this sector. Community expectations in relation to aquatic centres are rising and these spaces are associated with wellness and health. Energy consumption in indoor swimming pool buildings is high due to the high indoor air temperatures, increased ventilation heat losses and the need to disinfect water. This study investigates the energy consumption and indoor environmental quality of seven aquatic centres in Australia. The construction and various energy consuming systems of the facilities are analysed and compared against the energy consumption. Thermal comfort data is collected through measuring the indoor environmental parameters. Building envelopes were found to be leaky in most of the buildings resulting in energy wastage. The main indicators for energy consumption were gross floor area, area of pool surface, and number of visitors. It was found that the set point temperatures were significantly high in some of the buildings resulting in high level of discomfort for the spectators and staff.

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Information about indoor air temperatures in residential buildings is of interest for a range of reasons, e.g. the health and comfort of occupants, energy demand for space heating and cooling. To date there have been few long term studies that measure and characterise indoor air temperatures in Australian homes. New primary research undertaken by the authors measured temperatures in 273 homes over the period 2011 to 2014 in seven climate zones, from Melbourne in the south to Cairns in the north of Australia. Humidity data was also collected in 20 homes. This paper is a description of the data collected and the subsequent analysis.

Indoor temperatures were compared with outdoor temperatures and a mathematical model was fitted to the data. In general, monthly average indoor temperatures were found to be 2 degreesC higher than monthly average outdoor temperatures, apart from periods with consistently cold weather, where the monthly average outdoor temperature was less than 20 degreesC, which were found to have larger differences. The indoor temperature model developed has been compared with data measured by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in 438 homes in three Australian cities. The model developed using project measurements are highly consistent with the CSIRO data.

Further data collection compared indoor and outdoor humidity in 20 houses in Sydney and Melbourne. The indoor humidity ratio was found to be, on average, slightly higher than outdoors, but indoor levels generally track outdoor levels quite closely. This is likely due to the high air exchange rate in most houses.

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Context: Many heuristics-based indoor positioning approaches havebeen developed to enhance positioning estimation. However, thereis no comprehensive survey of these heuristics information and methods. 


Objective: The main objective of this study is to providea holistic view and an in-depth analysis ofwhat heuristics informationand methods have been used, their general achievements andlimitations. This study aims to provide a comprehensive summary tofacilitate further research on indoor positioning heuristics. 

Method: We conducted a systematic literature review (SLR) on indoorpositioning heuristics. 

Results: Ninety-three (93) primary studies wereselected. We found two general types of heuristics informationand four primary heuristics methods, which we summarised in thispaper. We also found that many of these positioning heuristics aretested in experimental settings only. Some heuristics claim practicalapplications but are not tested for the challenging and typical indoorenvironments. 

Conclusion: Most existing heuristics information andmethods rely on the assumptions that may not be true in real life environment, hence limiting the usefulness of the positioning outcomes. Based on the analysis of this SLR, we propose two research directions to enhance positioning estimation.