84 research outputs found
Sustainability assessment in residential high-rise building design: state of the art
No full textThis is an Accepted Manuscript of an article published by Taylor & Francis Group in Architectural Engineering and Design Management on 2022, available online at: http://www.tandfonline.com/10.1080/17452007.2022.2060931.Twenty-first-century population growth is raising the need for more land space in urban areas and this has led to the construction of high-rise buildings, reducing horizontal urban development and making construction of residential high-rise buildings (RHB) a necessity in major cities around the world. In this regard, urban density and high-rise construction are key factors when determining a city’s sustainability and the liveability of urban areas. Sustainability indicators were identified in previous research and quantification has proven to be a useful tool for RHB design. This paper provides an overview of the various sustainability factors applied to RHB design. The paper also compiles information on the sustainability strategy, description of RHB issues and how this type of building can affect urban design. Some strategies may improve the natural environment such as incorporating green spaces, combining living, working and leisure activities, providing facilities for children and the elderly such as playgrounds and reasonably natural settings, ease of access to public transport, road networks and shopping facilities and so forth. The research is based on a descriptive approach and it analyses previous studies. The findings show that the environmental, economic and social aspects of sustainable development (SD) should be considered to implement sustainability in RHBs. Previous literature reviews on RHBs considered social aspects in less detail.The author Maria del Mar Casanovas-Rubio is a Serra Húnter Fellow. The author Bahareh Maleki would like to thank the FPI-UPC grantsPeer ReviewedPostprint (author's final draft
IoT-Based Smart Classroom: Networking, BSc Graduation Project
No full textTechnology is playing an increasingly important role in education, partially thanks to emerging teaching methods such as hybrid education. Smart classrooms equipped with technology can make the lives of the educators and students easier, and aid in the switch to hybrid education. In this work we propose an IoT based smart classroom framework to create a base for smart classroom applications. Using this framework, multiple applications are manifested in the form of prototypes. One prototype introduces wireless sensor readout capabilities. The other prototype focuses on assisting the lecturer in a hybrid teaching setup. Using the prototype, the teacher is able to control whether online students are able to hear the students who are physically present and vice versa. The prototype also includes a way of indicating a question from an online student.Electrical Engineerin
IoT-Based Smart Classroom: Server: BSc Graduation Project
No full textIn this work, we propose an IoT smart classroom framework which will be the base for smart classroom and hybrid teaching applications. The prototype introduces sensor readout capabilities, with which temperature, humidity, and loudness in a classroom can be monitored. Furthermore, the prototype introduces capabilities to collect and display measurements. Additionally, this prototype will assist an educator in a hybrid teaching setup by offering additional functionality, namely notifying the educator of online questions and giving an overview of environmental measurements in the classroom. With this prototype, the educator is able to control whether the students online are able to hear physically present students and vice versa. The prototype also introduces a way to notify the educator of any questions from students attending online. The goal of this prototype is to make the first steps to improve the hybrid teaching environment by reducing the workload on the educator and by making it easier for online students to interact with the educator. This prototype is split into three theses, focusing on sensor hardware, the Bluetooth mesh network, and the server respectively. This work will have a higher focus on designing and creating a server for this prototype, which will collect and display sensor measurements.Electrical Engineerin
Digital Signal Processing of PPG: for evaluation of Atrial Fibrillation
No full textThe performance of wearable Photoplethysmogram (PPG) sensors is highly influenced by noise. This thesis describes the methods and results of designing a filtering systemfor PPG in context of Atrial Fibrillation (AF) detection. The developed work is an adaptive filtering system combined with a robust heart rate detection mechanism for validation of the proposed method. Additionally, the heart rate estimation can potentially be used to detect AF episodes using machine learning. Research has been done regarding an optimal reference signal for the adaptive filtering structure. Accelerometer data, being commonly used as reference signal for the noise did not showgood correlationwith the motion induced artefacts in the signal. Therefore, a reference for the signal component is generated from the PPG itself, which is achieved by applying a narrow bandpass filter. Here the center frequency is determined from an autocorrelation of the signal in a sliding-window. The optimal settings for the sliding window in AF context were found to be 2 seconds with 80% overlap. Furthermore, a comparison is made between NLMS, RLS and Kalman adaptive algorithms, in which RLS showed the best overall performance. The validation of the filtering structure is based on peak detection from the enhanced signal compared with the ECG reference peaks. The results indicates that the system significantly improves the heart rate error in signal disturbed by noise and during AF episodes
IoT-Based Smart Classroom: Hardware, BSc Graduation Project
No full textIn this work, we propose an IoT smart classroom framework which will be the base for smart classroom and hybrid teaching applications. The prototype introduces sensor readout capabilities, which can be used to monitor: temperature, humidity, and loudness in a classroom. Furthermore, the prototype introduces capabilities to collect and display measurements. Additionally, this prototype will assist an educator in a hybrid teaching setup by offering additional functionalities. With this prototype, the educator is able to control whether the students online are able to hear physically present students or not. The prototype also introduces a way to notify the educator of any questions from students attending online. The goal of this thesis is to make the first steps to improve the hybrid teaching environment by reducing the workload on the educator and by making it easier for online students to interact with the educator.The project is divided into three submodules. Each submodule designs a different part of the total project. This thesis focuses on the hardware of the system. The hardware that is used for audio recording, audio controlling, question indicating and climate monitoring. The other two subgroups discuss IoT communication, data storing and graphical displaying of data.Electrical Engineerin
Flexible Transparency With Smart Materials: A study on adaptive thin glass facade developed with Shape memory alloy
No full textOwing to the rapid development of construction materials in building industry, a tendency towards smart and light design solutions using modern architectural principles is growing noticeably. The ultra-thin glass is a relatively new material which could be replaced with the thicker glasses in traditional windows to create a new concept for the building. Its promising prospects due to its low weight and its ability to be bent could develop a novel adaptive glass panel concept as a breathing skin in the building. Adaption can be implemented using smart materials capable of inherently sensing and responding to environmental changes with a type of actuation action. In this research study, the advancements of smart material technologies have been elaborated, together with the feasibility of these materials in adaptive architecture aspect. In the end, a novel adaptive glass panel concept has been offered by means of shape-memory alloy (SMA) cables in order to create a breathing skin for façade. The panel has been placed as an inner and outer skin in the selected case study. Its validation has been assessed through Finite-element numerical studies and experimental tests. The structural efficiency of the panel is evaluated by analyzing several glass laminate configurations under bending for inside and outside the situation and taking into account the effects of ordinary wind pressures for the outside condition. Based on the current investigation, it is expected that valuable design proposals can be derived for this novel design concept.Architecture, Urbanism and Building Sciences | Building Technolog
Atrial fibrillation fingerprinting
No full textAtrial fibrillation (AF) is a common age-related cardiac arrhythmia. AF is characterized by rapid and irregular electrical activity of the heart leading to a higher risk of stroke and heart failure. During AF, the upper chambers of the heart, called atria, experience chaotic electrical wave propagation. However, despite the various mechanisms introduced in the literature, there is still an ongoing debate on a precise and consistent mechanism underlying the initiation and perpetuation of AF. Some studies show that AF is rooted in impaired electrical conduction and structural damage of atrial tissue, known as electropathology. Atrial electrograms (EGMs) recorded directly from heart’s surface, provide an important diagnostic tool to localize and quantify the degree of electropathology in the tissue. However, the analysis of the electrograms is currently constrained by the lack of suitable methods that can reveal the hidden electrophysiological parameters of the tissue. These parameters can be used as local indication of electropathology in the tissue. We believe that understanding AF and improving AF therapy starts with developing a proper forward model that is accurate enough (from a physiological point of view) and simultaneously simple enough to allow for subsequent parameter estimation. Therefore, the main focus of this thesis is on developing a simplified forward model that can efficiently explain the observed EGM based on AF relevant tissue parameters. An initial step before performing any analysis on the data is to remove noise and artefacts. All atrial electrogram recordings suffer from strong far-field ventricular activities (VA). Therefore, as the first step, we propose a new framework for removal of VA from atrial electrograms, which is based on interpolation and subtraction followed by low-rank and sparse matrix decomposition. The proposed framework is of low complexity, does not require high resolution multi-channel recordings, or a calibration step for each individual patient. In the next step, we develop a simplified electrogram model. We represent the model in a compact matrix form and show its linear dependence on the conductivity vector, enabling the estimation of this parameter from the recorded electrograms. The results show that despite the low resolution and all simplifying assumptions, the model can efficiently estimate the conductivity map and regenerate realistic electrograms, especially during sinus rhythm. In the next contribution of this dissertation, we propose a new approach for a better estimation of local activation times for atrial mapping by reducing the spatial blurring effect that is inherent to electrogram recordings using deconvolution. Employing sparsity based regularization and first-order time derivatives in formulating the deconvolution problem, improved performance of transmembrane current estimation is obtained. In the final part, we focus on translating our findings from research to clinical application. Therefore, we studied the effect of electrode size on electrogram properties including the length of the block line observed on the resulting activation map, percentage of observed low voltage areas, percentage of electrograms with low maximum steepness, and the number of deflections in the recorded electrograms.Signal Processing System
Atrial activation time estimation using cross-correlation between higher order neighboring electrodes: In epicardial electrograms
No full textA common cardiac arrhythmia is atrial fibrillation, which is becoming more widespread worldwide. Currently there is some understanding about the mechanisms behind atrial fibrillation, however more insight into the conduction of the atrial tissue is desired. Therefore, invasive mapping studies have been performed where an array of electrodes is used to record the electrical activity on the heart’s surface during open-chest surgery. The moment in time when the tissue under an electrode depolarizes, called the local activation time can be used to reconstruct the propagation pattern of the signal that triggers the tissue to contract. In this thesis, the application of the cross-correlation for estimation of the local activation time of the atria is investigated. Specifically, the benefits of not only cross-correlating electrode pairs that are close, but also pairs that are far away are evaluated. A framework is constructed, based on a graph, that defines these higher order neighboring pairs of electrodes. This is compared to the golden standard of using the steepest deflection of an electrogram, as well as to other methods using the cross-correlation. Experiments are done on simulated electrograms where the true activation times are available, as well as on natural data recorded from patients. Finally some future research is proposed to investigate for which morphologies the proposed cross-correlation based methods may be most effective.Electrical Engineering | Circuits and System
Local Activation Time Estimation in Fractionated Electrograms of Cardiac Mappings
No full textIn this study, we propose a novel approach for estimation of local activation times (LATs) in fractionated electrograms. Using an electrophysiological tissue model, we first formulate the electrogram array as a convolution of transmembrane currents with a distance kernel. These currents are more local activities and less affected by the heterogeneity in the tissue compared to electrograms. We then deconvolve the distance kernel with the electrograms to reconstruct the transmembrane current. To stabilize the solution of this ill-posed deconvolution, we use spatio-temporal total variation as a regularization. This helps to preserve sharp spatial and temporal deflections in the currents that are of higher importance in LAT estimation. Finally, the maximum negative slope of the reconstructed transmembrane currents are used to estimate the LATs. Instrumental comparison to two reference approaches shows that the proposed approach performs better in estimating the LATs in fractionated electrograms.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work publicSignal Processing System
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