This thesis summarizes the subject of intelligent homes and describes commonly used standards and commercial solutions on the market. The thesis covers the design of a low-cost and easy to use smart home system which can be managed over the internet, uses a genetic algorithm for heating regulation optimization and its central computing unit is a low-cost, embedded device with low power consumption. The functionality of the system is verified on a practical application of heating regulation in a house. The efficacy of the system for energy savings is shown; it is based on measured data statistics.

This thesis deals with DCS for bulding control. The main aim was to develop a general system, which can be adapted according to the individual requirements and which should minimize costs too. Hardware modules, communication bus, communication protocol, system topology and regulation mechanisms, have been designed. Regulators have been set. There are introduced current realization and possible future extensions too. The high security and the high functionality topics are included.

This final thesis deals with adaptive control of small brewery. Contains a short description of brewing technology and adaptive control. Includes design of small brawery and control system based on STM32F407 Cortex-M4 microcontroller. For online identification is used Recursive Least Squares Method. The controller function perform a modified PSD controller with filtered derivative component, reducing the first overshot and dynamic antiwindup. The proposed adaptive controller is implemented into microcontroller. Created device i used for semi-automatic beer production.

This thesis is theoretically described heating surfaces, radiators and regulation valves. There are also described their features, advantages and disadvantages and division according to design. The aim of the work is determine the dynamics characteristics of heating surfaces and radiators including control valves, which are parts of measurement panel. Based on the measurement are determined appropriate characteristics of which are calculated values for regulating. The result of this study can serve as a guide to the practical measurement method of dynamics characteristics of the real-working heating systems, or serve as a template for the settings according to the measured data.

Indiana University-Purdue University Indianapolis (IUPUI) / Heating, ventilation, and air conditioning (HVAC) is the technology responsible to maintain temperature levels and air quality in buildings to certain standards. In a commercial setting, HVAC systems accounted for more than 50% of the total energy cost of the building in 2013 [13]. New control methods are always being worked on to improve the effectiveness and efficiency of the system. These control systems include model predictive control (MPC), evolutionary algorithm (EA), evolutionary programming (EP), and proportional-integral-derivative (PID) controllers. Such control tools are used on new HVAC system to ensure the ultimate efficiency and ensure the comfort of occupants. However, there is a need for a system that can monitor the energy performance of the HVAC system and ensure that it is operating in its optimal operation and controlled as expected. In this thesis, an air handling unit (AHU) of an HVAC system was modeled to analyze its performance using real data collected from an operating AHU using a wireless monitoring system. The purpose was to monitor the AHU's performance, analyze its key parameters to identify flaws, and evaluate the energy waste. This system will provide the maintenance personnel to key information to them to act for increasing energy efficiency. The mechanical model was experimentally validated first. Them a baseline operating condition was established. Finally, the system under extreme weather conditions was evaluated. The AHU's subsystem performance, the energy consumption and the potential wastes were monitored and quantified. The developed system was able to constantly monitor the system and report to the maintenance personnel the information they need. I can be used to identify energy savings opportunities due to controls malfunction. Implementation of this system will provide the system's key performance indicators, offer feedback for adjustment of control strategies, and identify the potential savings. To further verify the capabilities of the model, a case study was performed on an air handling unit on campus for a three month monitoring period. According to the mechanical model, a total of 63,455 kWh can be potentially saved on the unit by adjusting controls. In addition the mechanical model was able to identify other energy savings opportunities due to set point changes that may result in a total of 77,141 kWh.