7,463 research outputs found

    Screening of energy efficient technologies for industrial buildings' retrofit

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    This chapter discusses screening of energy efficient technologies for industrial buildings' retrofit

    An experimental characterization of reservoir computing in ambient assisted living applications

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    In this paper, we present an introduction and critical experimental evaluation of a reservoir computing (RC) approach for ambient assisted living (AAL) applications. Such an empirical analysis jointly addresses the issues of efficiency, by analyzing different system configurations toward the embedding into computationally constrained wireless sensor devices, and of efficacy, by analyzing the predictive performance on real-world applications. First, the approach is assessed on a validation scheme where training, validation and test data are sampled in homogeneous ambient conditions, i.e., from the same set of rooms. Then, it is introduced an external test set involving a new setting, i.e., a novel ambient, which was not available in the first phase of model training and validation. The specific test-bed considered in the paper allows us to investigate the capability of the RC approach to discriminate among user movement trajectories from received signal strength indicator sensor signals. This capability can be exploited in various AAL applications targeted at learning user indoor habits, such as in the proposed indoor movement forecasting task. Such a joint analysis of the efficiency/efficacy trade-off provides novel insight in the concrete successful exploitation of RC for AAL tasks and for their distributed implementation into wireless sensor networks

    Fog computing for assisting and tracking elder patients with neurodegenerative diseases

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    U.S. hospitals transmit and manage great amounts of information with the avenue of Internet of things. This work departs from a real need detected by healthcare centers and hospitals in U.S., Spain and Ecuador. This work focuses on the application of fog computing for obtaining an app rich in visual content that will not overload U.S. hospital infrastructures even if it was used massively. The simulation results showed that the proposed fog-based approach could support a regular use (one day out of three on average) by 1% of patients of one of the most common neurodegenerative diseases in 14 states in U.S (i.e. 36, 400 patients in total) with only a traffic of 528 KB per day on average when using one hospital per state

    Designing for User Confidence in Intelligent Environments

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    Intelligent environments aim at supporting and assisting users in their daily activities. Their reliability, i.e., the capability of correctly accomplishing the intended tasks and of limiting or avoiding damage in case of malfunctions, is essential as for any user-facing technology. One aspect of reliability, often neglected, is guaranteeing the consistency between system operation and user expectations, so that users may build confidence over the correct behavior of the system and its reaction to their actions. The paper will review the literature concerning methodologies and tools that directly involve users and have been specifically applied or adopted for intelligent environments, throughout the entire design flow – from requirements gathering to interface design. The paper will then propose, building on top of the previous analysis, a set of guidelines that system designers should follow to ensure user confidence in their intelligent environments

    Development of a simulation tool for measurements and analysis of simulated and real data to identify ADLs and behavioral trends through statistics techniques and ML algorithms

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    openCon una popolazione di anziani in crescita, il numero di soggetti a rischio di patologia è in rapido aumento. Molti gruppi di ricerca stanno studiando soluzioni pervasive per monitorare continuamente e discretamente i soggetti fragili nelle loro case, riducendo i costi sanitari e supportando la diagnosi medica. Comportamenti anomali durante l'esecuzione di attività di vita quotidiana (ADL) o variazioni sulle tendenze comportamentali sono di grande importanza.With a growing population of elderly people, the number of subjects at risk of pathology is rapidly increasing. Many research groups are studying pervasive solutions to continuously and unobtrusively monitor fragile subjects in their homes, reducing health-care costs and supporting the medical diagnosis. Anomalous behaviors while performing activities of daily living (ADLs) or variations on behavioral trends are of great importance. To measure ADLs a significant number of parameters need to be considering affecting the measurement such as sensors and environment characteristics or sensors disposition. To face the impossibility to study in the real context the best configuration of sensors able to minimize costs and maximize accuracy, simulation tools are being developed as powerful means. This thesis presents several contributions on this topic. In the following research work, a study of a measurement chain aimed to measure ADLs and represented by PIRs sensors and ML algorithm is conducted and a simulation tool in form of Web Application has been developed to generate datasets and to simulate how the measurement chain reacts varying the configuration of the sensors. Starting from eWare project results, the simulation tool has been thought to provide support for technicians, developers and installers being able to speed up analysis and monitoring times, to allow rapid identification of changes in behavioral trends, to guarantee system performance monitoring and to study the best configuration of the sensors network for a given environment. The UNIVPM Home Care Web App offers the chance to create ad hoc datasets related to ADLs and to conduct analysis thanks to statistical algorithms applied on data. To measure ADLs, machine learning algorithms have been implemented in the tool. Five different tasks have been identified. To test the validity of the developed instrument six case studies divided into two categories have been considered. To the first category belong those studies related to: 1) discover the best configuration of the sensors keeping environmental characteristics and user behavior as constants; 2) define the most performant ML algorithms. The second category aims to proof the stability of the algorithm implemented and its collapse condition by varying user habits. Noise perturbation on data has been applied to all case studies. Results show the validity of the generated datasets. By maximizing the sensors network is it possible to minimize the ML error to 0.8%. Due to cost is a key factor in this scenario, the fourth case studied considered has shown that minimizing the configuration of the sensors it is possible to reduce drastically the cost with a more than reasonable value for the ML error around 11.8%. Results in ADLs measurement can be considered more than satisfactory.INGEGNERIA INDUSTRIALEopenPirozzi, Michel

    TABSAOND: A technique for developing agent-based simulation apps and online tools with nondeterministic decisions

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    Agent-based simulators (ABSs) have successfully allowed practitioners to estimate the outcomes of certain input circumstances in several domains. Although some techniques and processes provide hints about the construction of these systems, some aspects have not been discussed yet in the literature. In this context, the current approach presents a technique for developing ABSs. Its focus is to guide practitioners in designing and implementing the decision-making processes of agents in nondeterministic scenarios. As an additional technological innovation, the ABSs are deployed as both mobile apps and online tools. This work illustrates the current approach with two case studies in the fields of (a) health and welfare and (b) tourism. These case studies have also been developed with the most similar technique from the literature for comparing both techniques. The presented technique improved the simulated outcomes in terms of their similarity with the real ones. The obtained ABSs were more efficient and reliable for large amounts of agents (e.g. 10,000 – 400,000 agents). The development time was lower. Both the framework and the implementation of a case study are freely distributed as open-source to facilitate the reproducibility of the experiments and to assist practitioners in applying the current approach

    A User-Centred Methodology to Design and Simulate Smart Home Environments and Related Services

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    openI progressi nelle tecnologie di automazione e comunicazione all'interno degli edifici residenziali offrono molti interessanti vantaggi per lo sviluppo delle Smart Home, come l'aumento di efficienza energetica, il miglioramento il comfort per gli abitanti e la riduzione dei costi operativi per il proprietario. L'aggregazione e la condivisione dei dati all'interno delle reti possono essere garantite dal moderno approccio denominato Internet delle cose (IoT) e supportati dalle nuove tecnologie dell'informazione e della comunicazione (ICT). Tali tecnologie si stanno evolvendo e le abitazioni stanno diventando luoghi tecnologici popolati da una moltitudine di dispositivi in grado di raccogliere una grande quantità di dati e di cooperare in modo intelligente per controllare tutti i dispositivi connessi, come gli elettrodomestici, l'illuminazione, i sistemi di riscaldamento, ecc. Da un lato, l’intelligenza crescente dei dispositivi connessi produce una grande quantità di dati; dall'altro lato, la complessità di tali dati crea difficoltà di classificazione, trasmissione ed interpretazione delle informazioni utili. Entrambi gli aspetti possono ridurre drasticamente i potenziali vantaggi e limitare la diffusione dei cosiddetti dispositivi “smart”. Mentre a livello aziendale già esistono soluzioni di automazione affermate ed ampiamente utilizzate, le applicazioni per le abitazioni private sono ancora di difficile diffusione a causa della mancanza di standard di comunicazione e della presenza di dispositivi e sistemi altamente eterogenei e quindi di difficile integrazione. Inoltre, anche quando la connessione tra due dispositivi viene stabilita, renderli interoperabili è un’altra grande sfida a causa delle differenze nelle modalità di funzionamento e della difficoltà di integrazione dell'interfaccia. Infatti, le Smart Home non consentono ancora una elevata interoperabilità e gli studi fatti sono spesso fortemente orientati alla tecnologia e concentrati sulle potenzialità dei singoli sottosistemi, trascurando i benefici per gli utenti finali. A tale scopo, questo lavoro definisce un modello di gestione delle informazioni per ambienti domestici intelligenti con lo scopo di supportare la progettazione e la simulazione dei dispositivi “smart” nonché dei servizi sviluppati. Tale modello considera diverse tipologie di dispositivi, le relazioni esistenti tra loro, i flussi informativi e le modalità di interazione dell’utente per modellare correttamente l'ambiente e definirne il comportamento. Il modello sviluppato supporta la progettazione della Smart Home ed è in grado di simulare le funzionalità dei dispositivi con lo scopo finale di valutare i benefici dei servizi forniti.The advances in home automation and communication technologies offer several attractive benefits for the modern smart home, such as increased energy efficiency, improved residential comfort and reduced operative costs for the homeowner. Data aggregation and sharing within the networks can be guaranteed by modern Internet of Things (IoT) approaches and supported by available Information and Communication Technologies (ICT) tools. Such technologies are evolving and the private houses are becoming technological places populated by a multitude of devices able to collect a huge quantity of data and to cooperate in an intelligent way to control different domains, from household appliances to lighting or heating and ventilation. On one hand, the rising intelligence of smart devices makes a large amount of data available; on the other hand, data complexity creates difficulties in classifying, transmitting and interpreting essential data. Both aspects may drastically reduce the potential advantages and limit the diffusion smart devices. While in building automation proven solutions already exist, tailored applications for private houses and integration among heterogeneous devices and systems are still challenging due to the lack of standards and the variety of adopted communication protocols and data model schemas. Furthermore, even when the device connection and consolidation are achieved, making them cooperate in an interoperable way is another big challenge due to differences in usage paradigms, operation modes and interface integration. In fact, Smart Homes still lack of high interoperability and researches are often strongly technology-oriented and focused on single sub-system potentialities neglecting the expected benefits for the final users. For this purpose, the presented research defines an information management model for the smart home environment to support design and simulation of its devices as well as the enabled services. Such a model considers different device typologies, their mutual relationships, the information flows and the user interaction modalities in order to properly model the environment and define its behavior. It supports the design of the smart home by simulating the devices’ functionalities and estimating the expected performances.INGEGNERIA MECCANICA E GESTIONALEopenCapitanelli, AndreaCapitanelli, Andre
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