840 resultados para Smart Home Environment (SHE)


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Background Infant development is adversely affected in the context of postnatal depression. This relationship may be mediated by both the nature of early mother-infant interactions and the quality of the home environment. Aim To establish the usefulness of the Global Ratings Scales of Mother-Infant Interaction and the Infant-Toddler version of the Home Observation for the Measurement of the Environment (IT-HOME), and to test expected associations of the measures with characteristics of the social context and with major or minor depression. Method Both assessments were administered postnatally in four European centres; 144 mothers were assessed with the Global Ratings Scales and 114 with the IT-HOME. Affective disorder was assessed by means of the Structured Clinical Interview for DSM-IV Disorders. Results Analyses of mother-infant interaction indicated no main effect for depression but maternal sensitivity to infant behaviour was associated with better infant communication, especially for women who were not depressed. Poor overall emotional support also reduced sensitivity scores. Poor support was also related to poorer IT-HOME scores, but there was no effect of depression. Conclusions The Global Ratings Scales were effectively applied but there was less evidence of the usefulness of the IT-HOME. Declaration of interest None.

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Background and aims Evaluating status in patients with motor fluctuations is complex and occasional observations/measurements do not give an adequate picture as to the time spent in different states. We developed a test battery to assess advanced Parkinson patients' status consisting of diary assessments and motor tests. This battery was constructed and implemented on a handheld computer with built-in mobile communication. In fluctuating patients, it should typically be used several times daily in the home environment, over periods of about one week. The aim of this battery is to provide status information in order to evaluate treatment effects in clinical practice and research, follow up treatments and disease progression and predict outcome to optimize treatment strategy. Methods Selection of diary questions was based on a previous study with Duodopa® (DIREQT). Tapping tests (with and without visual cueing) and a spiral drawing test were added. Rapid prototyping was used in development of the user interface. An evaluation with two pilot patients was performed before and after receiving new treatments for advanced disease (one received Duodopa® and one received DBS). Speed and proportion missed taps were calculated for the tapping tests and entropy of the radial drawing velocity was calculated for the spiral tests. Test variables were evaluated using non-parametric statistics. Results Post-treatment improvement was detected in both patients in many of the test variables. Conclusions Although validation work remains, preliminary results are promising and the test battery is currently being evaluated in a long-term health economics study with Duodopa® (DAPHNE).

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Nella tesi vengono analizzati i diversi aspetti della domotica. Uno sguardo sulla storia, sulle caratteristiche sia funzionali che strutturali. Viene analizzato l'impatto che questa ha sull'uomo e sul suo stile di vita. Vengono messe a confronto Google ed Apple, nello specifico per quel che riguarda la loro risposta alla smart home: Nest ed HomeKit, sia a livello funzionale che di codice. In seguito all'analisi di API e documentazioni è emerso che entrambe le aziende offrono pressoché le medesime funzionalità, ma con piccole particolarità che fanno la differenza, dando inizio così ad una battaglia per il primato.

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Progettazione di un framework per ottimizzare l'efficienza energetica di una Smart home. Gestione e supervisione tramite smartphone Android

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Relazione completa delle scelte progettuali e implementative di un applicativo ad agenti sviluppato nel contesto Smart Home. Essa contiene un veloce riassunto dello scenario e dello stato attuale dell'applicazione, unitamente a un'introduzione sul middeware su cui si appoggia l'applicativo (TuCSoN). Segue quindi un'analisi delle scelte di modeling delle entita da gestire, le metodologie di supporto alla persistenza e un'ampia descrizione su come gli agenti comunichino tra loro e attraverso quali mezzi (centri di tuple). Quindi viene analizzata l'implementazione partendo dalle scelte implementative sino ad esaminare cosa avviene nel programma a seguito dell'interazione con l'utente. Infine le conclusioni a cui si e giunti e due appendici sulla terminologia e le classi presenti nel prototipo attuale.

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Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

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The purpose of this thesis was to investigate the association between parent acculturation and parental fruit and vegetable intake, child fruit and vegetable intake, and child access and availability to fruits and vegetables. Secondary data analysis was performed on a convenience sample of low-income Hispanic-identifying parents (n = 177) and children from a baseline survey from the Sprouting Healthy Kids intervention. T tests were used to examine the association between parent acculturation status (acculturated or non-acculturated) and fruit intake, vegetable intake and combined fruit and vegetable intake of both the parent and the child. T tests were also used to determine the relationship between parent acculturation and child access and availability to fruits, vegetables, and combined fruits and vegetables. Statistical significance was set at a p level of 0.05. The mean FVI for the parents and children were 3.41 servings and 2.96 servings, respectively. Statistical significance was found for the relationships between parent acculturation and parent fruit intake and parent acculturation and child fruit access. Lower acculturation of the parent was significantly related to higher fruit intake. Counter to the hypothesis, higher acculturation was found to be associated with greater access to fruits for the child. These findings suggest the necessity for not only culturally specific nutrition interventions, but the need for interventions to target behaviors for specific levels of acculturation within a culture. ^

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The deployment of the Ambient Intelligence (AmI) paradigm requires designing and integrating user-centered smart environments to assist people in their daily life activities. This research paper details an integration and validation of multiple heterogeneous sensors with hybrid reasoners that support decision making in order to monitor personal and environmental data at a smart home in a private way. The results innovate on knowledge-based platforms, distributed sensors, connected objects, accessibility and authentication methods to promote independent living for elderly people. TALISMAN+, the AmI framework deployed, integrates four subsystems in the smart home: (i) a mobile biomedical telemonitoring platform to provide elderly patients with continuous disease management; (ii) an integration middleware that allows context capture from heterogeneous sensors to program environment¿s reaction; (iii) a vision system for intelligent monitoring of daily activities in the home; and (iv) an ontologies-based integrated reasoning platform to trigger local actions and manage private information in the smart home. The framework was integrated in two real running environments, the UPM Accessible Digital Home and MetalTIC house, and successfully validated by five experts in home care, elderly people and personal autonomy.

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In this paper, the authors introduce a novel mechanism for data management in a middleware for smart home control, where a relational database and semantic ontology storage are used at the same time in a Data Warehouse. An annotation system has been designed for instructing the storage format and location, registering new ontology concepts and most importantly, guaranteeing the Data Consistency between the two storage methods. For easing the data persistence process, the Data Access Object (DAO) pattern is applied and optimized to enhance the Data Consistency assurance. Finally, this novel mechanism provides an easy manner for the development of applications and their integration with BATMP. Finally, an application named "Parameter Monitoring Service" is given as an example for assessing the feasibility of the system.

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Thesis (Master's)--University of Washington, 2016-06

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Analisi degli scenari applicativi in ambiente Home Manager e progettazione, implementazione e collaudo di alcune delle funzionalità proposte.

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To tackle the challenges at circuit level and system level VLSI and embedded system design, this dissertation proposes various novel algorithms to explore the efficient solutions. At the circuit level, a new reliability-driven minimum cost Steiner routing and layer assignment scheme is proposed, and the first transceiver insertion algorithmic framework for the optical interconnect is proposed. At the system level, a reliability-driven task scheduling scheme for multiprocessor real-time embedded systems, which optimizes system energy consumption under stochastic fault occurrences, is proposed. The embedded system design is also widely used in the smart home area for improving health, wellbeing and quality of life. The proposed scheduling scheme for multiprocessor embedded systems is hence extended to handle the energy consumption scheduling issues for smart homes. The extended scheme can arrange the household appliances for operation to minimize monetary expense of a customer based on the time-varying pricing model.