To make machines emotionally more intelligent, it is necessary to choose the right measuring devices that are able to collect physiological biosignals, which can be used to recognize the emotional state of the user. These devices should not restrict the users in their everyday life, therefore commercial, non-invasive Internet of Things (IoT) devices must be used. Thanks to the interoperability of IoT devices, it is possible to send the obtained data to a server, where it can be used in the predict method of a trained machine learning algorithm. Based on the recognized emotion, it is possible to create different instructions for smart home elements.

PREFACE The use of various digital and smart devices and systems has also become more and more part of people's daily lives, with the emergence of the human-machine interface as a tool to help them work in various activities. Digitalisation is one of the most significant trends and tendencies of our time, and can be seen as the next step in globalisation [1]. Media literacy is an umbrella term, similar to ICT [2] and new media phenomena have become increasingly visible. Digital technology-enhanced literacy, mediated by ICT systems, is thus playing an increasingly important role, with a growing impact on society, the economy and education, and its transformative effects. The essence of these phenomena is that the new cultural form is created and exists on a digital platform [3].Mobile technology, ambient intelligence, digital games, big data-based technologies and algorithms are an integral part of this world [4]. The study and systematisation of the digital transformative effects of all these phenomena is becoming increasingly vital and has a growing impact on the learning process. On the one hand, the process of digitalisation serves as an internal driving force for digital work-based educational processes, and on the other hand, it represents a major challenge for the different actors in educational systems and for learners.