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.

In the framework of Europe 2020 strategy for smart, sustainable and inclusive growth and of recent growth related theories we analyse the extent to which second-tier cities as growth poles contribute to the growth of the country with focus on EU member states. We conduct an analysis of the development of second-tier cities from the countries with similar level of development as Romania, with focus especially on employment related issues. The selection of growth poles will be done using clustering of EU member states for year 2010 based on the headline indicators from the Europe 2020 strategy (employment, research and development, climate change and energy sustainability, education, poverty and social exclusion) and resource productivity as lead indicator for resource efficiency, so as to highlight the different levels of development among EU countries. In order to ensure higher level of accuracy in clustering, from economic perspective we also include other indicators, such as GDP per capita and the index of economic freedom

Lately, the logistics sector has seen accelerated development, which has led to general economic growth, but, at the same time, it has caused considerable environmental damage due to the excessive consumption and emissions that are currently affecting society at large. Since logistics activities are considered some of the most polluting economic activities, this present article aims to present the advantages of implementing the green logistics concept. To this purpose, the activity of a logistics centre in Romania was analysed, with a focus on the greenhouse gases (GHGs) produced as a consequence of this economic activity, and its carbon footprint was calculated according to the GHG Protocol. Although this global standard is based on an integrated approach to how GHG emissions are calculated, there is limited evidence about its degree of implementation by companies. The results of the analysis revealed that the consumption of energy and fuel by the logistics sector has a significant impact on the environment. This impact is maintained, albeit at a smaller scale, even if the technology is replaced and the equipment used by companies to carry out their activities is increasingly performant.

Innovation has been a historical driver for progress. The need for more effective resource utilization has ignited the presence of many innovations in the economic environment. Among others, digitalization and internet connectivity are important pillars of development. Our paper aims to provide a few insights related to the question “How can we increase the efficiency of resource utilization in EU-28 countries through Eco-Innovation and Digital Inclusion?” This paper examines the issue of innovation related to the use of natural resources (Eco-innovation) as a determining factor in resource consumption in societies with different levels of digital inclusion. Our analysis is based on clustering of EU-28 Member States using three variables: the degree of digital inclusion, the Eco-Innovation Index, and the degree of resource use. We expect digital inclusion to mediate the relationship between eco-innovation and resource utilization. Clustering might reveal how the Eco-Innovation Index, Digital Inclusion Level, and Resource Productivity Index differ among EU-28 Member States and provide relevant information for prioritization of resource allocation at the EU level. Our approach of clustering based on the three variables considered reveals that countries with a better economy present better performance from the point of view of Digital Inclusion in the context of Eco-Innovation and the use of resources.

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.

Industrial development has implicitly led to the development of new systems that increase the ability to provide services and products in real time. Autonomous mobile robots are considered some of the most important tools that can help both industry and society. These robots offer a certain autonomy that makes them indispensable in industrial activities. However, some elements of these robots are not yet very well outlined, such as their construction, their lifetime and energy consumption, and the environmental impact of their activity. Within the context of European regulations (here, we focus on the Green Deal and the growth in greenhouse gas emissions), any industrial activity must be analyzed and optimized so that it is efficient and does not significantly impact the environment. The added value of this paper is its examination of the activities carried out by mobile robots and the impact of their electronic components on the environment. The proposed analysis employs, as a central point, an analysis of mobile robots from the point of view of their electronic components and the impact of their activity on the environment in terms of energy consumption, as evaluated by calculating the emission of greenhouse gases (GHGs). The way in which the activity of a robot impacts the environment was established throughout the economic flow, as well as by providing possible methods of reducing this impact by optimizing the robot’s activity. The environmental impact of a mobile robot, in regard to its electronic components, will also be analyzed when the period of operation is completed.