The IoT-embedded smart homes have a high level of home automation and could change many aspects of the residents' daily lives, such as control, convenience, comfort, and energy-saving. The rise of voice-based virtual assistants like Amazon's Alexa, Google assistants in the past five years has brought new potentials to provide occupants with a convenient and intuitive interface to interact with smart homes through conversations. However, the one-way communications in the form of user commands to control building systems does not result in the optimal course of actions. As such, in this thesis, we proposed the concept of proactive smart home assistants and explored the occupants' perception towards smart home assistants proactively providing suggestions to adapt them into energy-saving behaviors. We also investigated the impact of occupants' personal features on their intention in taking energy-saving behaviors. A comprehensive data collection was conducted through online surveys, in which 307 valid responses with participant's personal profile information, their perceptions of smart home assistants, and their feedback to our designed messages were collected. The first manuscript compared participants' responses to traditional plain-text energy-saving suggestions and suggestions provided by smart home assistants. The nudging effect of smart home assistants was justified to be significant in affecting occupant's energy-saving behaviors. Occupant's thermal comfort range, smart home device previous experience, values and beliefs were then proved to have significant impact on their intention in taking the smart home assistant's suggestions. The second manuscript fitted 21 personal characteristics features in machine learning models (SVM, Random Forest, Logistic Regression) to predict occupant's intention and attitude towards energy-saving suggestions. The results indicated that occupant's beliefs about interests in taking actions and beliefs about energy expenses, occupant's education level, residence occupancy type, thermal comfort ranges, and smart home device experiences are important features in occupants' energy-saving behavior intention prediction. This research demonstrates the effect of proactive smart home assistants in human-building interaction as well as the impact of personal characteristic features on occupant's energy-saving behaviors, paving a path to the future development of bi-directional human-building communication. / Master of Science / With the technology development in the fields of the Internet of Things (IoT), smart homes have made it possible to help occupants conserve energy in an efficient way without sacrificing the occupants' comfort. The rise of voice-based virtual assistants like Amazon's Alexa, Google assistants accompany the proliferation of smart speaker products in the past five years has brought new potentials to provide occupants with a convenient and intuitive interface to interact with smart homes through conversations. Based on IoT, the virtual assistants are able to control a broad range of Wi-Fi connected home devices like thermostats, lighting systems, and security systems. As such, through the simple wake words (e.g., "Alexa", "Hey, Google"), occupants can easily control the home environment with their voice commands. Despite the potentials brought by these voice-based virtual assistants, it has been shown that users might not know about all the supported features and limit their interaction with smart home assistants to simple daily tasks. The one-way communications in the form of user commands to control building systems do not result in the optimal course of actions. Therefore, in this study, we have envisioned that these virtual assistants, coupled with their corresponding smart home ecosystems could act proactively as a bridge to facilitate human-building interaction and achieve goals like nudging occupants to adopt sustainable and healthy behaviors. A comprehensive data collection was conducted through online surveys, in which 307 valid responses with participant's personal profile information, their perceptions of smart home assistants, and their feedback to our designed messages were collected. The first manuscript compared participants' responses to traditional plain-text energy-saving suggestions and suggestions provided by smart home assistants. The nudging effect of smart home assistants was justified to be significant in affecting occupant's energy-saving behaviors. Occupant's thermal comfort range, smart home device previous experience, values and beliefs were then proved to have significant impact on their intention in taking the smart home assistant's suggestions. The second manuscript fitted 21 personal characteristics features in machine learning models (SVM, Random Forest, Logistic Regression) to predict occupant's intention and attitude towards energy-saving suggestions. The results indicated that occupant's beliefs about interests in taking actions and beliefs about energy expenses, occupant's education level, residence occupancy type, thermal comfort ranges, and smart home device experiences are important features in occupants' energy-saving behavior intention prediction. This research demonstrates the effect of proactive smart home assistants in human-building interaction as well as the impact of personal characteristic features on occupant's energy-saving behaviors, paving a path to the future development of bi-directional human-building communication.

This dissertation deals with the platform Z-Wave. This platform tries to create an universal system for smart home. The theoretical part of the work describes in details the platform itself as well as the applicable libraries for programming of applications and the available equipments. The practical part presents the new custom gateway. The hardware of this gateway is designed with utilization of the Z-Wave module, Raspberry Pi 3 microcomputer, touchscreen, powerbank and the body of the system. The body has been designed in the Solid Works CAD system and printed on a 3D printer. The needed firmware was loaded into the Z-Wave module ZM5304 and this module has been interconnected with the Raspberry Pi 3 through the printed circuit board of the custom design. The gateway drives OpenZWave network through the new own application written with help of Python wrapper of the library OpenZWave and other open source components. The part of the work is also the list and description of the alternative commercial gateways available on the Czech market.

Internet Of Things (IoT) och hemautomation innebär möjligheten att koppla upp diverse enheter i ett hem gentemot internet, som därefter har som mål att underlätta och göra konsumenters vardag mer bekvämt. Hemautomation kan exempelvis handla om att låsa dörrar och tända lampor från en enda enhet (kontrollern), vilket underlättar då konsumenten inte behöver gå till vardera enhet för att utföra önskade aktiviteter. Kontrollers är den del av ett IoT-system inom hemautomation som agerar gränssnittet mellan konsumenten och enheterna.Open-source erbjuder konsumenter ett mer fritt nyttjande av produkter pga. dess öppna källkod. Många problem och frågor som uppstår i samband med dessa produkter härstammar inom området av säkerhet, samt vad som skiljer produkterna åt avseende säkerhet.Denna studie har samlat ihop sex open-source kontrollers och genomfört en jämförelse för att identifiera vilka kontrollers som uppnår säkerhet avseende konfidentialitet, integritet och tillgänglighet. Detta har utförts genom att identifiera vilka värden som förekommer i tidigare artiklar där säkerheten utvärderas för IoT och hemautomation, och för kontrollers.Studien kopplar ihop identifierade värden med CIA modellen, vilket står för confidentiality, integrity och availability (konfidentialitet, integritet och tillgänglighet). I samband med CIA modellen presenteras ett resultat där studiens aktuella kontrollers visar till vilken nivå de upprätthåller CIA modellen, baserat på det identifierade värden som fastställts. De kontrollers som förekommer i studien är Home Genie, OpenHAB, Home Assistant, Domoticz, Calaos och Pimatic.Studiens resultat erhålls via en litterär undersökning av 25 tidigare studier samt 12st tillkommande tekniska dokumentationer och forum för samtliga tillhörande kontrollers. Samtliga studier har blivit hämtade från databaserna Google Scholar, IEEE Xplore och ACM Digital Library och har därefter blivit analyserade och tematiskt kodade för vidare information. Totalt har studiens material genomgått urval i fem steg för att garantera relevant material som stämmer överens med studiens kriterier och mål för innehåll. Studiens resultat presenterar en ögonblicksbild som ger kunskap om jämförda kontrollers, specifikt i samband med CIA modellen, vilket belyser produkterna i samband för området av säkerhet avseende konfidentialitet, integritet och tillgänglighet. / Internet of Things (IoT) and home automation means the opportunity to connect various devices in a home to the Internet, which has the goal of facilitating and making consumers’ everyday lives more comfortable. For example, home automation could be about locking doors and lighting lamps from a single device (the controller), which may make it easier for the consumer since the consumer does not have to go to each device to perform the desired activity. Controllers are the part of a home automation IoT-system that acts as an interface between the consumer and the devices.Open-source offers consumers a freer use of products, due to its open-source code. Many problems and issues that arise in connection with these products originate in the field of security, as well as what distinguishes the products in terms of security.This study has collected six open-source controllers and conducted a comparison to identify which controllers achieve security regarding confidentiality, integrity and availability. This has been done by identifying the values that appear in previous articles where security is evaluated for IoT and home automation, and controllers.This study links identified values with the CIA model, which stands for confidentiality, integrity, and availability. In accordance with the CIA model, a result is presented where the study’s current controllers show to what level they maintain the CIA model, based on the identifies values established. The controllers that appears in this study are Home Genie, OpenHAB, Home Assistant, Domoticz, Calaos, and Pimatic.This study’s results are obtained through a literary study of 25 studies, and 12 additional technical documentations and information through forums for all the associated controllers. All studies have been retrieved from the Google Scholar database, IEEE Xplore, and ACM Digital Library, and subsequently analyzed and thematically coded for further information. In total, the material of this study has been selected in five steps to ensure relevant material that meets this study’s criteria and objectives for content. This study’s results present an overview that provides knowledge about compared controllers, specifically in connection with the CIA model which highlights the products in the field of security, regarding confidentiality, integrity, and availability.

The aim of this work was to create a module for home automation tools Home Assistant. The module is able to determine  which room is inhabited and estimate more accurate position of people inside the room. Known GPS location cannot be used for this purpose because it is inaccurate inside buildings and therefore one of the indoor location techniques needs to be used. Solution based on Bluetooth Low Energy wireless technology was chosen. The localization technique is the fingerprinting method, which is based on estimating the position according to the signal strength at any point in space, which are compared with a database of these points using machine learning. The system can be supplemented with motion sensors that ensure a quick response when entering the room. This system can be deployed within a house, apartment or small to medium-sized company to determine the position of people in the building and can serve as a very powerful element of home automation.

The aim of this thesis was to learn and summarize basic information about IoT systems, which protocols are used and introduction of Google Home system. The first part of the thesis describes the individual parts of the system --- microcontrollers, sensors, light elements and possible systems for backend. In the implementation part of the thesis was designed a solution for smart home controling using Google Home technology. Based on data from the weather station, the system controls and adjusts the intensity of outdoor lighting and controls the blinds. Furthermore, a control module for gate and garage door control is implemented. The system also takes care of vacuum cleaning in the house using iRobot Roomba vacuum cleaners with custom Wi-Fi module. The final part of the thesis summarizes the achieved results.