Integration of Internet of Things and Cloud computing. A case study on vital signs monitoring.

Il progresso scientifico e le innovazioni tecnologiche nei campi dell'elettronica, informatica e telecomunicazioni, stanno aprendo la strada a nuove visioni e concetti. L'obiettivo della tesi è quello d'introdurre il modello del Cloud computing per rendere possibile l'attuale visione di Internet of Thing. Nel primo capitolo si introduce Ubiquitous computing come un nuovo modo di vedere i computer, cercando di fare chiarezza sulla sua definizione, la sua nascita e fornendo un breve quadro storico. Nel secondo capitolo viene presentata la visione di Internet of Thing (Internet delle “cose”) che si avvale di concetti e di problematiche in parte già considerate con Ubiquitous computing. Internet of Thing è una visione in cui la rete Internet viene estesa agli oggetti di tutti i giorni. Tracciare la posizione degli oggetti, monitorare pazienti da remoto, rilevare dati ambientali sono solo alcuni esempi. Per realizzare questo tipo di applicazioni le tecnologie wireless sono da considerare necessarie, sebbene questa visione non assuma nessuna specifica tecnologia di comunicazione. Inoltre, anche schede di sviluppo possono agevolare la prototipazione di tali applicazioni. Nel terzo capitolo si presenta Cloud computing come modello di business per utilizzare su richiesta risorse computazionali. Nel capitolo, vengono inizialmente descritte le caratteristiche principali e i vari tipi di modelli di servizio, poi viene argomentato il ruolo che i servizi di Cloud hanno per Internet of Thing. Questo modello permette di accelerare lo sviluppo e la distribuzione di applicazioni di Internet of Thing, mettendo a disposizione capacità di storage e di calcolo per l'elaborazione distribuita dell'enorme quantità di dati prodotta da sensori e dispositivi vari. Infine, nell'ultimo capitolo viene considerato, come esempio pratico, l'integrazione di tecnologie di Cloud computing in una applicazione IoT. Il caso di studio riguarda il monitoraggio remoto dei parametri vitali, considerando Raspberry Pi e la piattaforma e-Health sviluppata da Cooking Hacks per lo sviluppo di un sistema embedded, e utilizzando PubNub come servizio di Cloud per distribuire i dati ottenuti dai sensori. Il caso di studio metterà in evidenza sia i vantaggi sia le eventuali problematiche che possono scaturire utilizzando servizi di Cloud in applicazioni IoT.

Development and in-vitro characterization of an implantable flow sensing transducer for hydrocephalus

An implantable transducer for monitoring the flow of Cerebrospinal fluid (CSF) for the treatment of hydrocephalus has been developed which is based on measuring the heat dissipation of a local thermal source. The transducer uses passive telemetry at 13.56 MHz for power supply and read out of the measured flow rate. The in vitro performance of the transducer has been characterized using artificial Cerebrospinal Fluid (CSF) with increased protein concentration and artificial CSF with 10\% fresh blood. After fresh blood was added to the artificial CSF a reduction of flow rate has been observed in case that the sensitive surface of the flow sensor is close to the sedimented erythrocytes. An increase of flow rate has been observed in case that the sensitive surface is in contact with the remaining plasma/artificial CSF mix above the sediment which can be explained by an asymmetric flow profile caused by the sedimentation of erythrocythes having increased viscosity compared to artificial CSF. After removal of blood from artificial CSF, no drift could be observed in the transducer measurement which could be associated to a deposition of proteins at the sensitive surface walls of the packaged flow transducer. The flow sensor specification requirement of +-10\% for a flow range between 2 ml/h and 40 ml/h. could be confirmed at test conditions of 37 degrees C.

Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Electric power grids throughout the world suffer from serious inefficiencies associated with under-utilization due to demand patterns, engineering design and load following approaches in use today. These grids consume much of the world’s energy and represent a large carbon footprint. From material utilization perspectives significant hardware is manufactured and installed for this infrastructure often to be used at less than 20-40% of its operational capacity for most of its lifetime. These inefficiencies lead engineers to require additional grid support and conventional generation capacity additions when renewable technologies (such as solar and wind) and electric vehicles are to be added to the utility demand/supply mix. Using actual data from the PJM [PJM 2009] the work shows that consumer load management, real time price signals, sensors and intelligent demand/supply control offer a compelling path forward to increase the efficient utilization and carbon footprint reduction of the world’s grids. Underutilization factors from many distribution companies indicate that distribution feeders are often operated at only 70-80% of their peak capacity for a few hours per year, and on average are loaded to less than 30-40% of their capability. By creating strong societal connections between consumers and energy providers technology can radically change this situation. Intelligent deployment of smart sensors, smart electric vehicles, consumer-based load management technology very high saturations of intermittent renewable energy supplies can be effectively controlled and dispatched to increase the levels of utilization of existing utility distribution, substation, transmission, and generation equipment. The strengthening of these technology, society and consumer relationships requires rapid dissemination of knowledge (real time prices, costs & benefit sharing, demand response requirements) in order to incentivize behaviors that can increase the effective use of technological equipment that represents one of the largest capital assets modern society has created.

An empirical examination of the integration of causal attribution and social learning theories in achievement situations

Using path analysis, the present investigation sought to clarify possible operational linkages among constructs from social learning and attribution theories within the context of a self-esteem system. Subjects were 300 undergraduate university students who completed a measure of self-esteem and indicated expectancies for success and minimal goal levels for an experimental task. After completing the task and receiving feedback about their performance, subjects completed causal attribution and self-esteem questionnaires. Results revealed gender differences in the degree and strength of the proposed relations, but not in the mean levels of the variables studied. Results suggested that the integration of social learning and attribution theories within a single conceptual model provides a better understanding of students' behaviors and self-esteem in achievement situations.