The blended learning method with its supporting electronic tools is a very well-known approach in academic education. In most of its practical applications, direct face to face contacts between students and the teacher as well as students with each other in groups are important elements in the organization of lectures and classes. This is of particular importance in conducting laboratory classes in teaching process for engineers. However, the COVID-19 lockdown in the spring of 2020 closed schools, universities and completely eliminated the possibility of direct interpersonal contacts. These extraordinary circumstances forced changes in the organization of the teaching process, in particular the introduction of distance learning. Therefore, this paper proposes a modified blended learning method as well as describes a case study on its introduction in the education of building automation engineers at a technical university. A new organizational structure of this modified method is presented, with discussion of tools and methods of active distance learning, introduced during the COVID-19 lockdown period. Finally, some experiences, general reflections along with the identification of the preferred forms of distance learning by students are presented. The future works are briefly described as well.

The street lighting is one of major components in total energy consumption in cities. The paper is focused on a concept of street lamp control systems and function organization with remote monitoring, to reduce maintenance costs and energy consumption. A new approach to the definition of functional strategy organization for outdoor lighting systems is introduced in the paper. Proposed functional strategies are based on four efficiency classes of building automation and control systems (BACS) defined in the EN 15323 standard. They have been formulated, analysed and eventually implemented and verified in real experiment street lighting installation. This outdoor lighting system, designed by the authors, based on LonWorks (the ISO/IEC EN 14908) platform with a power line communication aimed to control high-pressure sodium lamps. The street lamps are integrated nodes of a building management system (BMS). The results of experimental tests for the proposed functional strategies, implemented with various control scenarios, show that they provide a great potential in reducing energy consumption by street lighting installations. In particular, the energy use can be reduced even by 45 % in comparison to conventional street lighting system, especially without the use of monitoring and control.

Energy used for lighting is one of the major components of total energy consumption in buildings. Nowadays, buildings have a great potential to reduce their energy consumption, but to achieve this purpose additional efforts are indispensable. In this study, the need for energy savings evaluation before the implementation of lighting control algorithms for a specified building is highlighted. Therefore, experimental tests have been carried out in a university building with laboratories and other rooms, equipped with KNX building automation system. A dimmable control strategy has been investigated, dependent on daylight illuminance. Moreover, a relationship between external and internal daylight illuminance levels has been evaluated as well. Based on the experimental results, the authors proposed a method for the rough estimation of electrical energy savings. Since, according to the EN 15232 standard, Building Automation and Control Systems (BACS) play an important role in buildings’ energy efficiency improvements, the BACS efficiency factors from this standard have been used to verify the experimental results presented in the paper. The potential to reduce energy consumption from lighting in non-residential buildings by 28% for offices and 24% for educational buildings has been confirmed, but its dependence on specific building parameters has been discussed as well.

Energy efficient prosumer microgrids (PMGs) with active and flexible demand side management (DSM) mechanisms are considered to be crucial elements of future smart grids. Due to an increasing share of renewable energy and the growing power demand, appropriate tools to manage not only the loads but also small generation units, heating and cooling systems, storage units and electric vehicles should be provided for them. Therefore, this paper proposes an innovative approach to both physical and logical organization of an active DSM system for future building-integrated prosumer microgrids (BIPMGs), based on standard building automation and control systems (BACS) as well as Internet of Things (IoT) paradigm. New event-triggered control functions with developed universal, logical interfaces for open BACS and IoT network nodes are presented and their implementation in smart metering as well as fully integrated energy management mechanisms is analyzed. Finally, potential energy efficiency improvements with proposed BACS functions are discussed, based on BACS efficiency requirements defined in the EN 15232 standard.

In the context of the increasing integration of renewable energy sources (RES) and smart devices in domestic applications, the implementation of Home Energy Management Systems (HEMS) is becoming a pivotal factor in optimizing energy usage and reducing costs. This review examines the role of reinforcement learning (RL) in the advancement of HEMS, presenting it as a powerful tool for the adaptive management of complex, real-time energy demands. This review is notable for its comprehensive examination of the applications of RL-based methods and tools in HEMS, which encompasses demand response, load scheduling, and renewable energy integration. Furthermore, the integration of RL within distributed automation and Internet of Things (IoT) frameworks is emphasized in the review as a means of facilitating autonomous, data-driven control. Despite the considerable potential of this approach, the authors identify a number of challenges that require further investigation, including the need for robust data security and scalable solutions. It is recommended that future research place greater emphasis on real applications and case studies, with the objective of bridging the gap between theoretical models and practical implementations. The objective is to achieve resilient and secure energy management in residential and prosumer buildings, particularly within local microgrids.

Smart home and building systems are popular solutions that support maintaining comfort and safety and improve energy efficiency in buildings. However, dynamically developing distributed network technologies, in particular the Internet of Things (IoT), are increasingly entering the above-mentioned application areas of building automation, offering new functional possibilities. The result of these processes is the emergence of many different solutions that combine field-level and information and communications technology (ICT) networks in various configurations and architectures. New paradigms are also emerging, such as edge and fog computing, providing support for local monitoring and control networks in the implementation of advanced functions and algorithms, including machine learning and artificial intelligence mechanisms. This paper collects state-of-the-art information in these areas, providing a systematic review of the literature and case studies with an analysis of selected development trends. The author systematized this information in the context of the potential development of building automation systems. Based on the conclusions of this analysis and discussion, a framework for the development of the Generic IoT paradigm in smart home and building applications has been proposed, along with a strengths, weaknesses, opportunities, and threats (SWOT) analysis of its usability. Future works are proposed as well.