Wavelet-based filtration procedure for denoising the predicted CO2 waveforms in smart home within the Internet of Things

The operating cost minimization of smart homes can be achieved with the optimization of the management of the building's technical functions by determination of the current occupancy status of the individual monitored spaces of a smart home. To respect the privacy of the smart home residents, indirect methods (without using cameras and microphones) are possible for occupancy recognition of space in smart homes. This article describes a newly proposed indirect method to increase the accuracy of the occupancy recognition of monitored spaces of smart homes. The proposed procedure uses the prediction of the course of CO2 concentration from operationally measured quantities (temperature indoor and relative humidity indoor) using artificial neural networks with a multilayer perceptron algorithm. The mathematical wavelet transformation method is used for additive noise canceling from the predicted course of the CO2 concentration signal with an objective increase accuracy of the prediction. The calculated accuracy of CO2 concentration waveform prediction in the additive noise-canceling application was higher than 98% in selected experiments.Web of Science203art. no. 62

Novel proposal for prediction of CO2 course and occupancy recognition in Intelligent Buildings within IoT

Many direct and indirect methods, processes, and sensors available on the market today are used to monitor the occupancy of selected Intelligent Building (IB) premises and the living activities of IB residents. By recognizing the occupancy of individual spaces in IB, IB can be optimally automated in conjunction with energy savings. This article proposes a novel method of indirect occupancy monitoring using CO2, temperature, and relative humidity measured by means of standard operating measurements using the KNX (Konnex (standard EN 50090, ISO/IEC 14543)) technology to monitor laboratory room occupancy in an intelligent building within the Internet of Things (IoT). The article further describes the design and creation of a Software (SW) tool for ensuring connectivity of the KNX technology and the IoT IBM Watson platform in real-time for storing and visualization of the values measured using a Message Queuing Telemetry Transport (MQTT) protocol and data storage into a CouchDB type database. As part of the proposed occupancy determination method, the prediction of the course of CO2 concentration from the measured temperature and relative humidity values were performed using mathematical methods of Linear Regression, Neural Networks, and Random Tree (using IBM SPSS Modeler) with an accuracy higher than 90%. To increase the accuracy of the prediction, the application of suppression of additive noise from the CO2 signal predicted by CO2 using the Least mean squares (LMS) algorithm in adaptive filtering (AF) method was used within the newly designed method. In selected experiments, the prediction accuracy with LMS adaptive filtration was better than 95%.Web of Science1223art. no. 454

Methods of human activity classification in buildings

The number of smart homes is rapidly increasing. Smart homes typically feature functions such as voice-activated functions, automation, monitoring, and tracking events. Besides comfort and convenience, the integration of smart home functionality with data processing methods can provide valuable information about the well-being of the smart home residence. This study is aimed at taking the data analysis within smart homes beyond occupancy monitoring and detection of falling events of people. Two different approaches are proposed to integrate human activity recognition within smart homes. The first approach utilizes KNX standard-based devices to obtain room air quality data (humidity, CO2, temperature) and combine the obtained data with two wearable devices that provide movement-related data. The second approach simplifies, improves, and addresses a few of the shortcomings of the first approach, it utilizes different measuring devices with higher sampling rates. It examines multiple statistical methods and ultimately chooses a simpler multi-layer perceptron neural network model. Resulting in a less computationally intensive solution with higher accuracy levels. The study achieved cross-validation accuracy levels above 98 %.Chytrých domácností rychle přibývá. Inteligentní domy obvykle obsahují funkce, jako jsou hlasově aktivované funkce, automatizace, monitorování a sledování událostí. Kromě komfortu a pohodlí může integrace funkcí chytré domácnosti s metodami zpracování dat poskytnout cenné informace o pohodě rezidence chytré domácnosti. Tato studie je zaměřena na analýzu dat v inteligentních domácnostech nad rámec monitorování obsazenosti a detekce pádu osob. Jsou navrženy dva různé přístupy k integraci rozpoznávání lidské činnosti do inteligentních domácností. První přístup využívá zařízení založená na standardu KNX k získávání dat o kvalitě vzduchu v místnosti (vlhkost, CO2, teplota) a kombinování získaných dat se dvěma nositelnými zařízeními, které poskytují údaje související s pohybem. Druhý přístup zjednodušuje, zlepšuje a řeší několik nedostatků prvního přístupu, využívá různá měřicí zařízení s vyšší vzorkovací frekvencí. Zkoumá více statistických metod a nakonec volí jednodušší vícevrstvý model perceptronové neuronové sítě. Výsledkem je méně výpočetně náročné řešení s vyšší úrovní přesnosti. Studie dosáhla úrovně přesnosti křížové validace nad 98 %.450 - Katedra kybernetiky a biomedicínského inženýrstvívyhově

Application of a new CO2 prediction method within family house occupancy monitoring

The article describes the application of Python for verification of a newly designed method of CO2 prediction from measurements of indoor parameters of temperature and relative humidity within occupancy monitoring in real conditions of a family home. The article describes the implementation of non-electric quantities (indoor CO2 concentration, indoor temperature, indoor relative humidity) measurement in five rooms of a family home (living room, kitchen, children's room, bathroom, bedroom) using Loxone technology sensors. The IBM IoT (Internet Of Things) was used for storing and subsequent processing of the measured values within the time interval of December 22, 2018, to December 31, 2018. The devised method used radial basis function (artificial neural networks (ANN)) mathematical method (implementation in Python environment) to perform accurate predictions. For further increase of the accuracy and reduction of prediction noise from the obtained course of the predicted signal, multiple variations of the LMS adaptive filter algorithm (Sign, Sign-Sign, Sign-Regressor) were used (implemented in the MATLAB SW tool). The accuracy of the newly proposed CO2 concentration prediction method exceeds 95% in the selected experiments.Web of Science915877215876

Monitoring the quality of the indoor environment in the Intelligent Building

Práce se zabývá možností využití technologií KNX a BACnet pro provozní měření kvality vnitřního prostředí v inteligentní budově. Práce obsahuje návrh a realizaci provozního měření kvality vnitřního prostředí pomocí technologie KNX. Dále je zde uvedeno přesné referenční měření v inteligentní budově s využitím přístrojů od firmy Testo. Jsou zde popsány návody pro realizaci měření kvality vnitřního prostředí pomocí technologie KNX, BACnet a přístroji Testo. Naměřené hodnoty jsou vyhodnoceny vzhledem k daným normám a vyhláškám.This work deals with uses of KNX technology and BACnet technology for measuring indoor enviroment quality. This work contains desing and realisation for measuring indoor enviroment quality using KNX technology. Here is also stated accurate reference measurement in an intelligent building using Testo devices. This work contains manuals for measuring indoor enviroment quality using KNX, BACnet and Testo instruments. Measured values are evaluated with respect to current standards and regulations.450 - Katedra kybernetiky a biomedicínského inženýrstvívýborn

A Sustainable Revolution

The parties of the United Nations Framework Convention on Climate Change (UNFCCC) attained the Paris Agreement to tackle climate change and to strengthen the actions required for a sustainable transition towards an environmentally friendly future. This transition will involve holistic approaches and multifaceted societal shifts, requiring answers and collaboration between private, public, and academic sectors. This book gathers together contributions which study the transition towards a more sustainable future, involving and identifying the development and implications of more sustainable alternatives, in collaboration with all relevant stakeholders (e.g. communities, firms, policy makers, researchers, etc.), to achieve this transition. The approaches proposed are all concerned with a common perspective: imaging our globe with a greener picture, built upon a transversal sustainable revolution to clean up the Earth

Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-

Advances in Public Transport Platform for the Development of Sustainability Cities

Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings

SPATIAL TRANSFORMATION PATTERN DUE TO COMMERCIAL ACTIVITY IN KAMPONG HOUSE

ABSTRACT Kampung houses are houses in kampung area of the city. Kampung House oftenly transformed into others use as urban dynamics. One of the transfomation is related to the commercial activities addition by the house owner. It make house with full private space become into mixused house with more public spaces or completely changed into full public commercial building. This study investigate the spatial transformation pattern of the kampung houses due to their commercial activities addition. Site observations, interviews and questionnaires were performed to study the spatial transformation. This study found that in kampung houses, the spatial transformation pattern was depend on type of commercial activities and owner perceptions, and there are several steps of the spatial transformation related the commercial activity addition. Keywords: spatial transformation pattern; commercial activity; owner perception, kampung house; adaptabilit