Det ställs allt större krav på hållbarhet inom fastighetsbranschen vilket leder till att det blir mer aktuellt att nyttja digitala och energieffektiva lösningar för att uppfylla dessa. Begreppet smart byggnad har funnits länge men i takt med en snabb teknisk utveckling ändras vad som anses vara smart och det skiljer sig även åt för vem det berör. Syftet med studien är att undersöka vad en smart byggnad är och hur privatpersoner ställer sig till att köpa en bostadsrätt i en smart byggnad. Därav kommer begreppet smart byggnad först att redas ut i rapporten, både av vad som går att hitta i litteratur och även vad privatpersoner anser att en smart byggnad är. Det kommer även studeras vilka smarta funktioner som finns i en byggnad med bostadsrätter och vilka som är viktiga för privatpersoner vid ett köp av en lägenhet. Till att börja med har en litteraturstudie genomförts för att sedan följas upp av en digital enkätundersökning som riktar sig till privatpersoner. Enkätundersökningen innehåller flervalsfrågor samt ja/nej-frågor som berör smarta bostadsrätter. Respondenterna har delats in i tre kategorier, bostadssökande, bostadssökande som vill köpa bostadsrätt och icke bostadssökande. Resultatet visar att ungefär hälften av respondenterna har hört begreppet smart byggnad, men det varierar vad de tror en smart byggnad är samt vilka funktioner som är viktiga. Majoriteten anser att ett smart säkerhetssystem är den viktigaste smarta funktionen, medan den främsta anledningen till att vilja bo smart är bekvämlighet. Resultatet tyder dock på en bristande kunskap bland privatpersoner om vad en smart byggnad är och många bryr sig inte om att bo smart. / There are increasing demands on sustainability in the real estate industry, which makes it more relevant to use digital and energy-efficient solutions to meet these demands. The concept of smart building has existed for a long time. What is considered smart is changing due to the rapid technological development and varies for whom it affects. The purpose of the study is to investigate what a smart building is and individuals' views on buying a condominium in a smart building. Hence, the concept of smart building will first be sorted out in the report, both what can be found in the literature and what individuals consider a smart building to be. It will also be studied what type of smart features are present in a building with condominiums and which features are important for individuals when buying an apartment. To begin with, a literature study has been done and then followed up by a digital survey aimed at individuals. The survey contains multiple-choice questions as well as yes / no questions that concern smart condominiums. The respondents have been divided into three categories, housing applicants, housing applicants who want to buy a condominium, and non-housing applicants. The study shows that about half of the respondents have heard the term smart building, but it differs from what they think it is and which features are important. The majority believe that a smart security system is the most important smart feature, while the main reason for wanting to live in a smart building is convenience. However, the results indicate a lack of knowledge among the individuals about what a smart building is and that many do not care about living smart.

Hållbarhets- och klimatfrågor har varit aktuella under en längre period. Inom bygg- och fastighetssektorn har miljöcertifiering av byggnader kommit att bli ett verktyg för att arbeta med hållbar utveckling genom att effektivisera sektorns resursanvändning och minska dess klimatpåverkan. Det har de senaste åren varit en uppåtgående trend att miljöcertifiera byggnader. Det är inte omöjligt att investerare i framtiden kommer att ställa krav på att byggnader skall vara certifierade. Utöver det ökade intresset för miljöcertifieringar har det även uppkommit ett intresse kring certifiering av smarta byggnader. I februari 2017 började exempelvis EU-kommissionen att utveckla “Smart Readiness Indicator” vilken är tänkt att användas för att gradera hur smart en byggnad är. Syftet med uppsatsen är att ta fram faktorer som kan påverka viljan att investera i en certifiering som är inriktad på hur “smart” en byggnad är. En kvalitativ litteraturstudie samt en semistrukturerad intervju på distans har genomförts för att uppfylla uppsatsens syfte. Av litteraturstudien har det framkommit att smarta byggnader till stor del skapar liknande värden som miljöcertifierade byggnader gör, men att det i smarta byggnader även uppstår nya möjligheter till värdeskapande. Det har även från intervjuer framgått att det kommer påtryckningar från samhället och myndigheter som kan ge incitament till smarta byggnader. I diskussionen kopplas litteraturstudie och intervjuer ihop för att förklara vad som gör en byggnad smart samt beskriva vilka värden som uppstår för smarta byggnader och därmed blir faktorer som kan påverka viljan att investera i en certifiering som är inriktad på byggnaders smarthet. Uppsatsens slutsats är att de värden som uppstår för smarta byggnader utgör faktorer som kan påverka viljan att investera i en certifiering som är inriktad på byggnaders smarthet. De uppstående värden som smarta byggnader har gemensamt med miljöcertifierade byggnader kommer inte väga lika tungt som de värden som uppstår specifikt för smarta byggnader. Påtryckningar från samhället och myndigheter kan också komma att bli en stor faktor för valet att investera i en certifiering som är inriktad på byggnaders smarthet. / Sustainability and climate issues have been a hot topic for a longer period of time. Environmental certification of buildings has come to be a tool within the construction and real estate sector to work with sustainable development by making the use of resources within the sector more effective and by reducing its impact on the climate. There has been a rising trend in environmentally certifying buildings for the past couple of years. It is not impossible that investors will demand that buildings should be certified in the future. In addition to the increased interest in environmental certifications an interest in certification of smart buildings has also arisen. For example, in February of 2017 the European Commission began to develop “Smart Readiness Indicator” which is intended to be used for rating how smart a building is. The purpose of this study is to identify factors that may affect the willingness to invest in a certification which focus on how “smart” a building is. A qualitative literature study and one semi-structured interview has been carried out to fulfill the purpose of this study. From the literature study it has emerged that smart buildings create similar values to those created by environmentally certified buildings, however smart buildings also create new opportunities for value creation. Through interviews it has also emerged that there is pressure from society and authorities that can provide incentives for smart buildings. The literature study and the information from the interviews is combined in the discussion section of this study to explain what makes a building smart and to describe what values arise for smart buildings. These values are the factors that can affect the willingness to invest in a certification which focus on the smartness of a building. The conclusion of this study is that the values that arise for smart building constitute factors that can affect the willingness to invest in a certification which focuses on the smartness of a building. The emerging values that smart buildings and environmentally certified buildings have in common will not weigh as heavily as the values that arise specifically for smart buildings. Pressure from society and authorities may also become a major factor in the choice to invest in a certification which focuses on how smart a building is.

Le bâtiment est un noeud énergétique important et un support idéal pour développer etanalyser les effets d’un système de gestion optimisée d’énergie (SGEB) tant son impactpotentiel sur la demande énergétique globale est important. Cependant, pour que ces objectifssoient atteints, plusieurs verrous doivent être levés. Au-delà des problématiques liées àl’architecture de distribution, aux modèles (y compris ceux relatifs au comportement desusagers), aux outils de dimensionnement, à la formalisation des paramètres, contraintes etcritères, aux systèmes de production et aux modes de connexions au réseau de distribution, lesproblèmes liés à la mise en oeuvre d’un outil de gestion décentralisée et à sa validation sontcentraux centrale. Ces travaux s’inscrivent directement dans cette optique. Ils portent enparticulier sur l’élaboration de modèles énergétiques, de stratégies de gestion d’énergie dansune configuration multi-sources et multi-charges et surtout de mise en oeuvre de méthodes etd’outils de validation au travers de bancs tests variés où certains composants peuvent êtreréels.Ce travail analyse le gestionnaire énergétique « G-homeTech » comprenant plusieursfonctionnalités de gestion testées sur des bancs d’essai virtuels et hybrides qui permettent decombiner à la fois des composants matériels et logiciels dans les simulations. Cela a permisd'insérer des actionneurs communicants pour tester leur pertinence. Les validations menéesmontrent que le gestionnaire énergétique permet l'effacement de pointes de consommation etdes économies sur la facture énergétique globale tout en respectant les contraintes techniqueset réglementaires.Les évènements prédits ne sont pas toujours ceux qui se produisent. Nous avons alorssimulé de telles situations. La radiation solaire et la consommation totale des services noncontrôlables sont différentes de celles prédites. Cette différence a conduit à des dépassementsde puissance électrique souscrite qui a activé le mécanisme de gestion réactive du gestionnaireénergétique. Des ordres de délestage sont alors dynamiquement envoyés à certainséquipements. Ces ordres alimentent directement les modèles des équipements électriques.Selon les importances relatives données au coût et au confort, nous avons montré que legestionnaire énergétique permet de faire des économies substantielles en évitant lesconsommations durant les pics de prix et évitant les dépassements de souscription pareffacement, par modulation du fonctionnement des systèmes de chauffage et par décalage defonctionnement des services temporaires dans les périodes plus intéressante énergétiquement. / The building is an important energy node and an ideal support to develop and analyzethe effects of an Energy Management System (EMS). Because of its potential impact, such amanagement of global energy demand is important. However, to achieve these goals, severallocks must be removed. Beyond issues related to the distribution architecture, to models(including those relating to user behavior), sizing tools, the formalization of parameters,constraints and criteria, production systems and methods of connection to the grid, problemrelated to implementation of decentralized management tool and its validation are central. Mywork is part of this context. It focuses in particular on the development of energy models,strategies for energy management in a multi-source and multi-load configuration, andespecially, the implementation methods and the validation tools through various test bencheswhere some components are real.This paper analyzes the energy manager “G-homeTech” including several managementfeatures tested on virtual and hybrid test benches that combine both hardware and softwarecomponents in the simulations. This has put communicating actuators to test their relevance.The validations show that the energy manager allows the deletion of peak demand andsavings on the overall energy bill while respecting the technical and regulatory constraints.Predicted events are not always those that occur. We then simulated such situations.Solar radiation and the total consumption of uncontrollable services are different from thosepredicted. This difference has led to over-subscribed electric power which has enabled themanagement mechanism of reactive energy manager. Load shedding orders are thendynamically sent to certain equipement. These orders directly supply models of electricalequipment.According to the relative importance given to cost and comfort, we have shown that theenergy manager can make substantial savings avoiding consumption during price peaks andavoiding over-subscription by erasure, by modulation of heating system operation and byshefting the timed service operation in the most interesting periods in energy.

Le bâtiment devient de plus en plus un système complexe où les flux énergétiques doivent être gérés en fonction des usages : on parle de bâtiments intelligents. Il s'ensuit une complexité croissante pour les concepteurs, qui doivent s'intéresser autant au bâtiment lui-même (plusieurs sources électriques et multiplication des charges) qu'à ses équipements, sa gestion énergétique mais aussi aux interactions avec l'environnement extérieur (flux d'informations exogènes sur le marché d'énergie, prix d'achat et de revente, subventions à l'auto-consommation, etc...). Il est désormais nécessaire de coupler la phase de conception avec celle de gestion énergétique du bâtiment. Les travaux de cette thèse visent à proposer une démarche méthodologique permettant de formuler automatiquement les problèmes d'optimisation exploitables autant en conception qu'en exploitation du système bâtiment. La démarche est basée sur les concepts issus de l'ingénierie dirigée par les modèles (IDM). / The building is becoming increasingly a complex system where energy flows must be managed according to consumption: we talk about intelligent buildings. This means increasing complexity for designers who need to focus as much on building itself (several power sources and multiplication of charges) in its equipment, and in its energy management but also to interactions with the external environment (exogenous flow of information on the energy market, the purchase price and resale, subsidies for self-consumption, etc. ...). It is now necessary to tie the design phase with that of building energy management. The work of this thesis aims at proposing a methodological approach to automatically formulate optimization problems at design stage and under operation of building. The approach is based on concepts from the model-driven engineering (MDE).

<p>Due to the rapid development of wireless communication and network technology, more and more wireless devices (e.g., Siemens, Lutron, etc.) are used in residential and commercial buildings. The wireless system has many advantages that traditional wired-based systems do not have, such as time-saving deployment and easy maintenance. However, the wireless system is also vulnerable to cyber-attacks since the data packets are transmitted by radio waves rather than by physical medium. The current cyber detection system (e.g., Intrusion detection system) monitors the data traffic to identify the anomalies in the network. However, it is unable to detect the attacks that tamper with the control logic or operating parameters, which results in the malfunction of the system. This thesis developed an integrated, cyber-security framework for cyber-attack detection in smart buildings.</p> <p>The objective of this research is to develop an integrated cyber-security framework for wireless-based smart building systems to protect buildings from the cyber-attacks. The wireless-based smart building systems are operated and controlled by either a two-position or continuous controlled approach. The efforts in this study have developed a cyber-security framework to deal with both two-position control and continuous control. For the two-position controlled smart buildings, the developed cyber-security framework integrates the data and models of both cyber and physical domains of building systems to detect faults, abnormal operations, and cyber attacks. The cyber-security framework developed for the continuous controlled system combines a data-driven model for detecting the faults of sensor measurements and a physical model based on engineering principle (e.g., laws of thermodynamics or control logic) to detect the anomaly of system operation.</p> <p>To develop the cyber-security frameworks, the testbeds corresponding to the two-position and continuous wireless systems were constructed for attack-oriented tests. A wireless-based lighting system for smart homes was used as the testbed for the study of the two-position control. It has a wireless occupancy sensor, an actuator for the light switch, and an open-source operating platform (OpenHAB) for system control and monitor. The platform of the wireless is the ZigBee. An indoor shading system at a living lab in new Herrick building at Purdue University was utilized as the testbed for the study of the continuous controlled system. The indoor shading system exploits the roller shades to block the excess daylighting to provide an acceptable illuminance condition for occupants. The shading system uses the wireless illuminance sensor, weather condition, and wire-based controller to automatically operate the shades for the acceptable illuminance. </p> <p>The study implemented designed cyber-attacks to validate the effectiveness of the developed frameworks. The final results show that the developed two models were able to detect the attacks effectively (95-100% attacks identified and isolated). The abnormal operations tested in two-position control system were identified when an abnormal state was triggered, or the modelled state and real state did not match in the finite state machine model developed. For continuous control, the abnormal operations were detected when there is a significant deviation between the modelled measurement and the actual measurement. The cybersecurity framework developed in the thesis demonstrates an effective approach for detecting system faults caused by attacks. The frameworks could be widely used for other different building systems and beyond buildings, such as transportation or industrial manufacturing systems.</p>

IoT har blivit en stor producent av big data. Big data kan användas för att optimera operationer, för att kunna göra det så måste man kunna extrahera användbar information från big data. Detta kan göras med hjälp av neurala nätverk och maskininlärning, vilket kan leda till nya typer av smarta applikationer. Den här rapporten fokuserar på att besvara frågan hur bra är neurala nätverk på att förutspå sensor värden och hur pålitliga är förutsägelserna och om dom kan användas i verkliga applikationer. Sensorlådor användes för att samla data från olika rum och olika neurala nätverksmodeller baserade på LSTM nätverk användes för att förutspå framtida värden. Dessa värden jämfördes sedan med dom riktiga värdena och absoluta medelfelet och standardavvikelsen beräknades. Tiden som behövdes för att producera en förutsägelse mättes och medelvärde och standardavvikelsen beräknades även där. LSTM modellerna utvärderades utifrån deras prestanda och träffsäkerhet. Modellen som endast förutspådde ett värde hade bäst träffsäkerhet, och modellerna tappade träffsäkerheten desto längre in i framtiden dom försökte förutspå. Resultaten visar att även dom enkla modellerna som skapades i detta projekt kan med säkerhet förutspå värden och därför användas i olika applikationer där extremt bra förutsägelser inte behövs. / The IoT is becoming an increasing producer of big data. Big data can be used to optimize operations, realizing this depends on being able to extract useful information from big data. With the use of neural networks and machine learning this can be achieved and can enable smart applications that use this information. This thesis focuses on answering the question how good are neural networks at predicting sensor values and is the predictions reliable and useful in a real-life application? Sensory boxes were used to gather data from rooms, and several neural networks based on LSTM were used to predict the future values of the sensors. The absolute mean error of the predictions along with the standard deviation was calculated. The time needed to produce a prediction was measured as an absolute mean values with standard deviation. The LSTM models were then evaluated based on their performance and prediction accuracy. The single-step model, which only predicts the next timestep was the most accurate. The models loose accuracy when they need to predict longer periods of time. The results shows that simple models can predict the sensory values with some accuracy, while they may not be useful in areas where exact climate control is needed the models can be applicable in work areas such as schools or offices.

No description available.

Le bâtiment est un noeud énergétique important et un support idéal pour développer et analyser les effets d'un système de gestion optimisée d'énergie (SGEB) tant son impact potentiel sur la demande énergétique globale est important. Cependant, pour que ces objectifs soient atteints, plusieurs verrous doivent être levés. Au-delà des problématiques liées à l'architecture de distribution, aux modèles (y compris ceux relatifs au comportement des usagers), aux outils de dimensionnement, à la formalisation des paramètres, contraintes et critères, aux systèmes de production et aux modes de connexions au réseau de distribution, les problèmes liés à la mise en oeuvre d'un outil de gestion décentralisée et à sa validation sont centraux centrale. Ces travaux s'inscrivent directement dans cette optique. Ils portent en particulier sur l'élaboration de modèles énergétiques, de stratégies de gestion d'énergie dans une configuration multi-sources et multi-charges et surtout de mise en oeuvre de méthodes et d'outils de validation au travers de bancs tests variés où certains composants peuvent être réels. Ce travail analyse le gestionnaire énergétique " G-homeTech " comprenant plusieurs fonctionnalités de gestion testées sur des bancs d'essai virtuels et hybrides qui permettent de combiner à la fois des composants matériels et logiciels dans les simulations. Cela a permis d'insérer des actionneurs communicants pour tester leur pertinence. Les validations menées montrent que le gestionnaire énergétique permet l'effacement de pointes de consommation et des économies sur la facture énergétique globale tout en respectant les contraintes techniques et réglementaires. Les évènements prédits ne sont pas toujours ceux qui se produisent. Nous avons alors simulé de telles situations. La radiation solaire et la consommation totale des services non contrôlables sont différentes de celles prédites. Cette différence a conduit à des dépassements de puissance électrique souscrite qui a activé le mécanisme de gestion réactive du gestionnaire énergétique. Des ordres de délestage sont alors dynamiquement envoyés à certains équipements. Ces ordres alimentent directement les modèles des équipements électriques. Selon les importances relatives données au coût et au confort, nous avons montré que le gestionnaire énergétique permet de faire des économies substantielles en évitant les consommations durant les pics de prix et évitant les dépassements de souscription par effacement, par modulation du fonctionnement des systèmes de chauffage et par décalage de fonctionnement des services temporaires dans les périodes plus intéressante énergétiquement.

La sociedad está siendo testigo de una revolución digital que ha generado cambios en diversos ámbitos. Uno de estos cambios es la construcción de o la transformación de edificios comunes a Smart Buildings, lo que puede conseguir que varios aspectos como la seguridad, el consumo energético, entre otros, se gestionen de forma más eficiente. El desarrollo de Smart Buildings es acompañado del desarrollo de las tecnologías IoT (Internet of Things), las cuales son una opción de soporte para convertir un edificio en inteligente. El IoT, entre sus beneficios, permite que los entornos tecnológicos y físicos se puedan integrar y ha sido ampliamente involucrado en diversas industrias e iniciativas. Asimismo, entre sus áreas de aplicación se encuentra el ser utilizado para que los Smart Buildings puedan recopilar datos que les indiquen qué accionar realizar automáticamente. Siendo así, entre aquellas áreas donde el IoT tendría impactos significativos están la construcción, operación y administración de edificios para facilitar servicios, brindar funcionalidades eficientes y avanzar hacia objetivos de sostenibilidad. Por otra parte, el uso de arquitecturas tecnológicas ha permitido que varias empresas hayan logrado aprovechar las tecnologías de la información de forma óptima en sus procesos de mitigación de riesgos, capacidad de cambios en sus sistemas organizacionales, entre otros. Siendo así, la motivación del proyecto yace en brindar una arquitectura tecnológica para las implementaciones de Smart Buildings con IoT que permita a las organizaciones contar con un diseño guía y que puedan cambiar sus componentes según la complejidad y exigencia de sus requerimientos. / Society is witnessing a digital revolution that has caused changes in several fields. One of these changes is the construction of or the transformation of traditional buildings into Smart Buildings, which can ensure that many aspects such as security, energy consumption, among others, are managed efficiently. The development of Smart Buildings is followed by the development of IoT (Internet of Things) technologies, which are a support option to turn a building into a smart one. The IoT, among its benefits, allows technological and physical environments to be integrated and has been widely involved in various industries and initiatives. Also, among its areas of application is being used so that Smart Buildings can collect data that tells them what to do automatically. Thus, among those areas where the IoT would have significant impacts are the construction, operation, and administration of buildings to facilitate services, provide efficient functionalities and advance towards sustainability objectives. On the other hand, the use of technological architectures has conceded various companies to achieve optimal use of information technologies in their risk mitigation processes, the ability to change their organizational systems, among others. Thus, the motivation of the project lies in providing a technological architecture for the implementation of Smart Buildings with IoT that allows organizations to have a guide design and that they can change their components according to the complexity and requirement of their requirements. / Trabajo de investigación

<p>This paper aims to present a novel approach to real-time indoor temperature forecasting to meet energy consumption constraints in buildings, utilizing computing resources available at the edge of a network, close to data sources. This work was inspired by the irreversible effects of global warming accelerated by greenhouse gas emissions from burning fossil fuels. As much as human activities have heavy impacts on global energy use, it is of utmost importance to reduce the amount of energy consumed in every possible scenario where humans are involved. According to the US Environmental Protection Agency (EPA), one of the biggest greenhouse gas sources is commercial and residential buildings, which took up 13 percent of 2019 greenhouse gas emissions in the United States. In this context, it is assumed that information of the building environment such as indoor temperature and indoor humidity, and predictions based on the information can contribute to more accurate and efficient regulation of indoor heating and cooling systems. When it comes to indoor temperature, distributed IoT devices in buildings can enable more accurate temperature forecasting and eventually help to build administrators in regulating the temperature in an energy-efficient way, but without damaging the indoor environment quality. While the IoT technology shows potential as a complement to HVAC control systems, the majority of existing IoT systems integrate a remote cloud to transfer and process all data from IoT sensors. Instead, the proposed IoT system incorporates the concept of edge computing by utilizing small computer power in close proximity to sensors where the data are generated, to overcome problems of the traditional cloud-centric IoT architecture. In addition, as the microcontroller at the edge supports computing, the machine learning-based prediction of indoor temperature is performed on the microcomputer and transferred to the cloud for further processing. The machine learning algorithm used for prediction, ANN (Artificial Neural Network) is evaluated based on error metrics and compared with simple prediction models.</p>