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This diploma thesis deals with creation of data-oriented 3D city model. The aim is to show potential of 3D data in the field of 3D city models and to develop a methodology of conversion of 3D-data with no information to data oriented 3D city model. For this purpose has been chosen format CityGML, which is well-known in the field of 3D city models. This format allows us to store semantical, topological and visual information besides geometry. In terms of concept, thesis is divided into two parts. First part is focused on theory, where are mentioned 3D supported formats. Further I deal with categories of city models according to its usage in praxis and theory about structure of CityGML and its advantages. In second part, I deal with the process of data conversion and its processing. I used geometric data of city parts Líšeň and Nový Lískovec and energy data of some blocks of flats. In the end of thesis, I summarize all the results, possible usage and development of the model.

An essential part of combating climate change is to reduce energy consumption. As the industrial sector was accountable for approximately a third of the total global carbon dioxide equivalents in 2019, it is crucial for industries to manage their energy usage. Research within the field of eco-feedback shows that visualising energy data can inspire energy reductions and promote knowledge. The thesis investigates how a dashboard for energy data visualisations for the industrial sector can be designed to be usable and to inspire behavioural change for its end users. Usability is researched in terms of initial learnability and subjective satisfaction. Perceived behavioural change is studied through changes in users' awareness and attitude towards energy management.  A prototype of a dashboard for energy data visualisations is developed through three iterations of the HCD process. During the first iteration, a paper prototype is developed, and evaluated through a workshop. During the second iteration, the paper prototype is translated into a digital prototype, which is then translated into a software prototype. The software prototype is evaluated through end-user tests at the end of the second iteration. During the third iteration, the software prototype is improved, based on the input from the previous evaluation, and then evaluated through end-user tests. The usability of the software prototype is evaluated through the think-aloud method and a SUS questionnaire. Perceived behavioural change is evaluated by interviewing the test users about their change in attitude and awareness after using the dashboard.  The thesis finds that the dashboard prototype was easy to use and interpret. The following design choices were concluded to contribute to the usability in terms of initial learnability and subjective satisfaction: visually separating information, information adjacency, adding explanatory texts, using colour as a visual encoding, using a colour scheme that provides contrast and consistency, filtering data through multi-select, providing different options for visualisation, using interactivity for further data exploration, giving the user response to actions, considering chart junk and the data-ink ratio, and using unambiguous icons. In addition, the thesis concludes that the dashboard inspired changes in both the user's awareness and attitude towards energy management. The design choices that were proven to affect the user's awareness and attitude were: letting the user choose their preferred unit to represent the data, presenting the user with tips, providing internal and external data comparisons, visualising multiple energy-related key figures, allowing for historic comparison, reminding the user of upcoming activities, presenting a list of scheduled measures and providing feedback of a prognosticated proposed measure in terms of its intended effects.

Syftet med studien är att utveckla ny kunskap om behovet som finns för energidata i ett industriföretag som verkar inom järn- och stålsektorn. Studien bidrar på så sätt till en djupare förståelse för faktorer som begränsar eller ökar en organisations förmåga att använda energidata. Användning av energidata har hög verksamhetsrelevans inom vald näringslivsgren eftersom det finns en konkurrensfördel i att ständigt effektivisera resurs- och energianvändningen i produktionsprocesser. Studien angriper energidata ur ett holistiskt perspektiv och utreder behovet i tre olika organisationsnivåer i delar av en energiintensiv produktionsprocess. Genom tillämpning av en kvalitativ metod, och tre åtskilda semistrukturerade djupintervjuer söktes svar på vad som begränsar eller hjälper en organisations medarbetare att bli mer engagerade i arbetet med energieffektivisering med hjälp av energidata. Resultatet visar att det finns ett behov av att synliggöra och visualisera energidata på arbetsplatsen för att öka allmänintresset för organisationens energianvändning. En respondent anser att energinyckeltal ökar i relevans och ger ett ökat engagemang om det anpassas till den mottagare som adresseras. Vidare ansåg en av respondenterna att ledningen borde öka efterfrågan av energidata för att förmedla att organisationens energikostnad prioriteras. En tydligare efterfrågan från ledningen skulle på så vis kunna stimulera till en ökad användning av energidata i det ständiga förbättringsarbetet. Fortsatt forskning behövs för att utveckla kartläggningsmetodiken ytterligare med målet att kunna generalisera behovet på organisationen som helhet. I en sådan forskningsstudie vore det lämpligt att genom en kvantitativ metod utforma en enkät som grundar sig i den empiri som inhämtats i föreliggande studie, för att sedan samla data ur en representativ population av organisationens medarbetare. / The purpose of the study is to identify, analyse and present an organisational need of energy data in an industrial company operating in the steel sector. Thus, the researcher develops an in-depth understanding of factors that cause limitations or increase an organisation's ability to use energy data. The business relevance of using energy data is significant in order to create competitive advantages and continuously improve the resource efficiency in energy-intensive manufacturing processes. The study was carried out using a qualitative method and it approaches energy data from a holistic perspective, auditing its use or not use in three organisational levels within an energy-intensive manufacturing process. To collect empirical data, three semi-structured interviews were carried out to find out what limits or helps an organisation's employees to become more involved in energy issues by the means of energy data. The results highlight the need to visualize energy data in the working place area as a way to increase public interest in the organisation. Furthermore, respondents felt that the energy performance indicators must be adapted to specific functions in order to gain relevance and increase the commitment of employees. One of the respondents expressed that top management should request energy data more often to give a clear signal that the organisation's energy cost is highly prioritized. A clear demand from management would thus encourage co-workers to use energy data in a continuous improvement process. The results of the study cannot be applied to all employees within each organisational level of the company. Through the qualitative method, the author developed a unique understanding of how energy data are used in the specific situation of three respondents. This knowledge opens the way to increase the validity of future studies. Further research should aim to generalize the needs of the organisation as a whole. In such a research study, it would be appropriate to use a quantitative method to design a questionnaire based on the empirical data gathered in this study.

Energy demand forecasting has been more vital in recent years with countries setting goals to become climate neutral by 2050. Indeed, energy demand forecasting allows the understanding of drivers of the energy demand in all sectors of the economy. It also allows the planning of transformation of the future energy system. This study focuses on forecasting energy demand in Europe using a multi-country bottom-up modelling approach. The work explores ways of collecting large quantity of data to feed an energy model and method of completion for missing data series. It also aims at studying attributes that make a model user friendly and easy to use for the modelling of several countries. A model and a database are developed to answer these questions. A case application is conducted on the specific topic of the phase out of internal combustion engines in the EU to validate model dynamics and practical use. It is found that an energy demand forecasting model is easier and more time efficient to use with an included historical database. The case study shows that multi-country modelling can be relevant for policy assessment. Finally, improvements and future developments are proposed for the present work. / Prognoser för energiefterfrågan har blivit allt viktigare under de senaste åren i och med att länder har satt upp mål om att bli klimatneutrala senast 2050. Prognoser för energiefterfrågan gör det möjligt att förstå drivkrafterna bakom energiefterfrågan inom alla ekonomiska sektorer. Det gör det också möjligt att planera omvandlingen av det framtida energisystemet. Denna studie fokuserar på prognoser för energiefterfrågan i Europa med hjälp av en bottom-up-modelleringsmetod för flera länder. I arbetet undersöks olika sätt att samla in stora mängder data för att mata en energimodell och metoder för att komplettera saknade dataserier. Det syftar också till att studera attribut som gör en modell användar vänlig och lätt att använda för modellering av flera länder. En modell och en databas utvecklas för att besvara dessa frågor. För att validera modellens dynamik och praktiska användning genomförs en fallstudie om utfasningen av förbränningsmotorer i EU. Det visar sig att en modell för prognostisering av energiefterfrågan är enklare och mer tidseffektiv att använda med en inkluderad historisk databas. Fallstudien visar att modeller för flera länder kan vara relevanta för policybedömning. Slutligen föreslås förbättringar och framtida utveckling för det aktuella arbetet.

Doctoral thesis deals with professional laundry care process and reduction of energy intensity and use of other operational commodities used in the process. Professional laundry care process is a specific energy intensive process; its purpose is to re-establish original properties of the now dirty laundry so that it may fulfil its functions again. This is basically a recycling and regeneration process comprising many sub-operations. Key operation is washing of the laundry in a washing bath, which removes impurities from the laundry. This thesis describes the most common technology of impurities removal, which is washing in a hot washing bath in cooperation with mechanical work and detergents. However, all of the described procedures may also be applied on alternative technologies, such as ozone washing, washing with low-temperature enzymes and ultrasound. Water is applied in all these technologies as a soaking agent. Water must have appropriate properties and must be removed from the laundry after the washing process in subsequent operations (drying, ironing, and pressing). Theoretical introduction of the thesis describes professional laundry care process in detail, and continues with mathematical modelling of the process and its main sub-operations (washing, drying) using mass and heat balance, and data acquisition and their application in research and development. Thesis further describes design of information system on the basis of relational database controlled by web application. This system enables to organize data and information from various sources – measured experimental data, data concerning measurement devices, operational records of machines, etc. Thesis further proposes how to evaluate and reduce energy intensity of a process. Descriptions are validated by examples and case studies. Key section of the thesis is a chapter describing experimental infrastructure. This infrastructure integrates several instalments of laundry equipment and is a fully functional operation of industrial laundry facility with 500kg/shift capacity, which serves as a model of energy intensive process. Sophisticated infrastructure and data acquisition system allows measuring wide spectrum of physical entities and examining factors influencing energy intensity of processes, and relationships between these factors as well as effectiveness of various savings measures in real life facilities.