Air pollution has become the most important issue concerning human evolution in the last century, as the levels of toxic gases and particles present in the air create health problems and affect the ecosystems of the planet. Scientists and environmental organizations have been looking for new ways to combat and control the air pollution, developing new solutions as technologies evolves. In the last decade, devices able to observe and maintain pollution levels have become more accessible and less expensive, and with the appearance of the Internet of Things (IoT), new approaches for combating pollution were born. The focus of the research presented in this paper was predicting behaviours regarding the air quality index using machine learning. Data were collected from one of the six atmospheric stations set in relevant areas of Bucharest, Romania, to validate our model. Several algorithms were proposed to study the evolution of temperature depending on the level of pollution and on several pollution factors. In the end, the results generated by the algorithms are presented considering the types of pollutants for two distinct periods. Prediction errors were highlighted by the RMSE (Root Mean Square Error) for each of the three machine learning algorithms used.

The evolution of technology brings closer the endless possibilities of education, allowing a human to learn something new anywhere and anytime. With the crisis created by the pandemic situation for the last two years, new ways of education have taken form to maintain the flow of learning and qualification; thus, the term “distance learning” has been implemented in all types of learning, from primary education all the way to tertiary education. This paper covers the image of tertiary education, mostly at the level of universities. Many changes took form at this level, such as developing new ways for the distance learning implementation by creating new programs dedicated for this new method of education. We will present to you how these changes took form and how they can evolve with the help of various technologies such as Blockchain and XR, and other strategic learning methods such as Massive Open Online Courses (MOOCs) and gamification. Universities start to create new programs based on their unique crypto coin, which help students pay for their studies, such as articles, new disciplines, and exchange programs. The gamification of these programs raises the interactivity that students have during class hours, thus motivating them and creating an optimal curve of learning, combined with the implementation of XR technology.

Textiles are a sophisticated and ancient technology with many appealing qualities. They are frequently soft and are readily folded, twisted, sliced, or deformed. When under tension, textiles can hold their shape and can even be manufactured to have different degrees of stretchability. Smart wearables and IoT-based clothing have the potential to have a significant impact by balancing functionality and the joy that fashion brings, along with the rise of the Internet of Things (IoT). It is now possible to easily fabricate both soft materials with embedded flexibility and stiff objects with embedded flexibility by combining textiles and 3D printing. In order to reinvent technology that can anticipate wants and desires, smart clothing tries to strike a balance between engineering, cybersecurity, interface, fashion, user experience, design, and science. The increasing merging of textiles and electronics now allows for the seamless and widespread integration of sensors into textiles, and conductive yarns have been developed to make this possible.