Sport has become a fundamental socio-economic area. Currently, technological progress plays one of the most important roles in the development of sport. In the twenty-first century, innovation, and technology are significantly shaping the world of law enforcement and sports policing, and huge changes are taking place that need to be responded to. The development, spread and completion of info communication, information technology, digital technologies, and digitalization itself at an ever-faster pace than ever before are fundamentally changing all areas of the economy and society. Today there is no question that digitalization is the engine of the economy, which has an impact in all sectors, including sports and law enforcement. In the study, the authors examine the possibility of technical development in the field of sports safety. Among other things, drones, facial recognition systems and predictive analytics will be examined. The methodology used is mainly based on the analysis and examination of previous methods. The authors propose to adapt the innovative tools used at previous sports and mass events in the field of sports safety.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

As the technical support for economic activities and social development, standards play a great role in modern society. However, with the increasing digitization of various industries, the traditional form of standards can no longer meet the needs of the new era, and there is an urgent need to digitally transform standards using advanced technologies. The digital transformation of standards involves the standard itself and all stages of its life cycle, is a very complex systematic project, in the transformation process, technology plays a key role. Therefore, this paper summarizes the key technologies involved in the process of digital transformation of standards, sorted out and evaluated them according to different purposes for which they were used, while giving the digitalization of standards transformation technology development trends and planning as well as typical cases, hoping to provide a comprehensive and clear perspective for those engaged in the related work, as well as reference for the subsequent research and application of digital transformation of standards.

The holding of soccer events has an important impact on modern urban activities, which is conducive to the economic development, social harmony, cultural integration and regional integration of cities. However, massive energy is consumed during the event preparation and infrastructure construction, resulting in an increase in the city’s carbon emissions. For the sustainable development of cities, it is important to explore the theoretical mechanism and practical effectiveness of the relationship between soccer events and urban carbon emissions, and to adopt appropriate policy management measures to control carbon emissions of soccer events. With the development of green technology, digitalization, and public transportation, the preparation and management methods of soccer events are diversified, and the possibility of carbon reduction of the event is further increased. This paper selects 17 cities in China from 2011 to 2019 and explores the complex impact of soccer events on urban carbon emissions by using green technology innovation, digitalization level and public transportation as threshold variables. The results show that: (1) Hosting soccer events increases carbon emissions with an impact coefficient of 0.021; (2) There is a negative single-threshold effect of green innovation technology, digitalization level and public transportation on the impact of soccer events on carbon emissions, with the impact coefficients of soccer events decreasing by 0.008, 0.01 and 0.06, respectively, when the threshold variable crosses the threshold. These findings will enhance the attention of city managers to the management of carbon emissions from soccer events and provide guidance for reducing carbon emissions from soccer events through green technology innovation, digital means and optimization of public transportation.

The integration of digitalization and servitization has become a significant trend in transforming the manufacturing industry due to digital intelligence technology. This paper examines the impact of the integration of digitalization and servitization on the performance of manufacturing companies and how small-scale enterprises can promote digital transformation leading to servitization. The study involved surveying 331 manufacturing companies in China using a seven-point Likert scale questionnaire. Measurement scales were validated using confirmatory factor analysis and discriminant validity tests. Mediation analysis assessed digitalization’s impact on servitization and firm performance. The study’s findings emphasize the significant impact of digitalization and servitization on enterprises’ performance. Digitalization plays a crucial role in mediating this relationship. The study highlights three critical dimensions of digital variables, including digital technology, digital labor, and digital relationship resources, essential in enabling effective servitization. Manufacturing enterprises generally prefer aligning their technology investments and organizational changes within the digitalization framework to implement servitization successfully. The study suggests two integration strategies, namely conservative and aggressive. The finding emphasizes that the convergence of digitalization and servitization leads to a new manufacturing production mode called digital servitization.

This paper discusses the use of workforce ecosystems to manage human intellectual capital. The need for work ecosystems has emerged in the digital age because of the rapid growth in the number of engaged partners and freelancers in the digitalization of enterprises. It is shown that this growth is directly related to the use of agile management systems in design and development: agile, DevOps, microservice architecture, turquoise practices, etc. The information systems needed to manage workforce ecosystems should have competency-based metrics to link business needs, recruitment and training, and finding new partners. At the same time, training should be prioritized over recruitment and the search for new partners in the context of staff shortages. When automating workforce ecosystems, a platform approach should be used to integrate both corporate HR, time and business process management systems, and similar systems from partners.