Resource Monitoring Research Articles

Use of ecotoxicological bioindicators in effluent monitoring — legal implications in Brazil

ABSTRACT Environmental changes directly influence quality of life, and environmental protection laws arise to ensure the maintenance of ecological balance. Aquatic environments have been contaminated by substances of anthropic origin, which are called effluents. Improper disposal of effluents has adverse effects on the environment and human health. In Brazilian legislation, the resolutions of the National Council for the Environment (CONAMA) RE 357/2005 and RE 430/2011 address the use of indicator species to evaluate the effluents’ toxicity. Despite these, much still needs to be done to control and monitor the emission of effluents in Brazilian water resources. The objective of this work was to carry out a historical survey of the regulations on the disposal of effluents in Brazil and to show the differences in each state's regulations, highlighting the indicator species accepted in each regulation and their advantages and disadvantages. In this way, this review summarizes and organizes the information of the Brazilian legislation on the disposal of effluents and helps the researcher in the area to choose between the methodologies adopted for the analysis of their environmental samples. Despite the insertion of bioassays, it is evident that the current Brazilian legislation is permissive, requiring adaptations and definitions to increase adherence to the ecotoxicological monitoring of water resources by the States.

Physiochemical Characteristics Analysis of Garrah River Water at Shahjahanpur, Ganga River Basin, Uttar Pradesh, India

This study focuses on the physiochemical analysis of the Garrah River in Shahjahanpur, within the Ganga River Basin, Uttar Pradesh, India. The research evaluates the impact of various pollutants, including industrial and municipal sewage, on the river's water quality. Water samples were collected from three locations along the river, representing different pollution levels. The analysis included parameters such as pH, dissolved oxygen (DO), total suspended solids (TSS), color, odor, electrical conductivity, temperature, chemical oxygen demand (COD), salinity, and the concentrations of various elements. The findings showed variations in water quality parameters, with DO, TSS, COD, and heavy metals indicating significant pollution, particularly downstream. Color and odor also suggested pollution from nearby industries. The study revealed that some parameters exceeded WHO standards for drinking water, raising concerns about health risks from exposure to contaminants like chromium. Urgent actions are required to treat municipal sewage and industrial effluents before discharging into the Garrah River. This research highlights the need for ongoing monitoring and sustainable management of water resources in the Ganga River Basin to protect the ecosystem and local communities. It underscores the importance of improving water quality in the region.

APPLICATION OF IOT PROTOCOLS IN SURFACE WATER POLLUTION MONITORING SYSTEMS

The rapid pace of industrial growth and the rise in consumerism are increasingly contributing to the deterioration of water quality, posing significant risks to both ecological systems and human health. The urgent need for effective monitoring of water resources to mitigate pollution and ensure the sustainability of these vital ecosystems has never been more apparent. The integration of Internet of Things (IoT) technologies into surface water monitoring presents a transformative approach to addressing these challenges. By automating the collection and transmission of data on water quality, IoT technologies offer a leap forward in our ability to efficiently monitor and manage environmental health. This article explores the application of various data transmission protocols, including Wi-Fi, Zigbee, LoRa, NB-IoT, and BLE, in the context of IoT-enabled water resource monitoring systems. Considerable attention was paid to determining the physical conditions of operation and the limitations they impose on the functioning of water monitoring systems. Each protocol is examined for its potential advantages and limitations in terms of energy efficiency, transmission range, and reliability under the specific conditions encountered in surface water monitoring. Through a comparative analysis, this study not only highlights the distinctive features and suitability of each protocol but also proposes a comprehensive framework for selecting the most appropriate technology based on the specific requirements of water monitoring projects. The findings of this research underscore the critical role of IoT technologies in advancing environmental monitoring and offer valuable insights for the development of more effective and sustainable water quality management strategies.

Enabling 6G Applications in the Sky: Aeronautical Federation Framework

While the current deployment of 5G is concentrated on high-quality service delivery on a two-dimensional terrestrial area covering our planet's surface, ongoing 5G standardization already addresses parts of the third dimension with 5G Non Terrestrial Networks (5G-NTN). 6G is expected to further leverage aeronautical communication towards a full exploration and comprehensive unification of all three dimensions. In this way, future communication systems will not only encompass all kinds of aeronautical platforms such as satellites, High- Altitude Platforms (HAPs), civil aircrafts, (self-)flying taxis, and UAVs but shall also enable the unification of terrestrial and non-terrestrial networks on a service platform level. This is further challenging, due to the rather closed aeronautical systems so far. We believe that emerging technology concepts such as Mobile Edge Computing (MEC) and Software-Defined Networking (SDN) can provide a basis for the full integration of aeronautical systems into their terrestrial counterpart. However, these technologies render the management and orchestration of aeronautical systems complex. As a step towards the integration of aeronautical communication and services into 6G, we propose a framework for the collection, monitoring, and distribution of resources in the sky among heterogeneous flying objects. This enables high-performance services for a new era of 6G aeronautical applications. Based on our proposed Aeronautical Federation Framework, we introduce emerging application use cases including aeronautical edge computing, aeronautical sensor networks, and aircraft cabin networks. In turn, we derive research challenges for 6G aeronautical networks.

Возраст и рост обыкновенного судака Sander lucioperca в разнотипных водоемах юга Западной Сибири

The age and growth of fish are the most important characteristics underlying the assessment of the state of fish stocks and the forecasting of future catches. The pike-perch Sander lucioperca (Linnaeus, 1758) is an alien fish species in Western Siberia. It was first introduced into the Ob basin in 1956. The introduction of this species into the Novosibirsk reservoir was carried out in 1959-1964, and into Lake Chany in 1964-1966. Currently, pike-perch is spread throughout the Ob basin and is an important fishery target. This study summarizes long-term data from the Novosibirsk branch of Russian Federal Research Institute of Fisheries and Oceanography ("VNIRO") about the growth of different-aged individuals of the pike-perch, collected during monitoring of aquatic biological resources in the Novosibirsk reservoir (54°20' N, 81°57'E) and Lake Chany (54°55'N, 77°31'E) over the last 10 years (2013-2022). These water bodies are of different types: the Novosibirsk reservoir was formed on the Ob River, the maximum depth reaches 25 m, the average depth is 8 m. The area of the reservoir is 1.07 thousand km^. Lake Chany is located in the Ob-Irtysh interfluve, drainless, filled due to the runoff of the Kargat and Chulym rivers, atmospheric precipitation and groundwater. The maximum depth is up to 8 m, average depth is 2 m. The area of the lake fluctuates greatly from year to year depending on the water level, in the long-term aspect it has tends to decrease, currently amounting to about 2 thousand km. The lake water has increased mineralization in most of the reaches. Fish collection for analysis of size characteristics is carried out annually from commercial catches. The total volume of material for this study was 2953 individuals from Lake Chany and 1102 individuals from the Novosibirsk reservoir. As a result of this work, it was found that in commercial catches in different types of water bodies in the south of Western Siberia, pike-perch has been known at the age of up to 14+ years over the last 10 years. In Lake Chany, there were mostly individuals of age groups 2+-4+, and in the Novosibirsk Reservoir - 3+-6+ (See Fig. 1). The pike-perch size of the same age from commercial catches varies greatly from one year to the next in Lake Chany, and in the Novosibirsk reservoir (See Fig. 2). It confirms the data on significant variability in growth rates of this species and indicating the need for a cautious approach to comparing the length and weight of pike perch in different observation periods. On average, over the last decade, pike-perch in Lake Chany is characterized by a slightly shorter standard length and greater weight than in the Novosibirsk Reservoir, however, the differences reach statistical significance (p < 0.001) only when comparing fish aged 2+ by standard length (See Fig. 3). The analysis of the relationship between the growth rate of pike-perch and environmental temperature showed that the absolute increase per year of standard length and weight of younger age groups fish in the Novosibirsk Reservoir has a statistically significant positive correlation with the temperature in April (r = 0.6110.775), and in Lake Chany - in May (r = 0.633-0.737) (See Tables 1, 2). Considering that the average April temperature in the area of the Novosibirsk reservoir is 1.9°C higher than in the area of Lake Chany, probably, in the latter, juvenile pike-perch begins to actively feeding a little later. It may explain the smaller sizes of pike-perch of younger age groups in Lake Chany compared to the Novosibirsk reservoir. The article contains 4 Figures, 2 Tables and 28 References. The authors express their gratitude to all colleagues - employees of the Novosibirsk Branch of "VNIRO", who over in different years took part in collecting the material. The Authors declare no conflict of interest.

Monitoring of land resources: reasons for the spread of exogenous geological processes

Monitoring of land resources: reasons for the spread of exogenous geological processes

Improving Surveillance in a Barangay: A Study on Assessing Needs for Designing Optimal Closed-Circuit Television Camera Placement

This study aimed to conduct a needs assessment in order to design a CCTV camera placement plan in a barangay to enhance community safety and security. Employing a descriptive research design, the study involved 300 randomly selected respondents from a barangay in Talugtug, Nueva Ecija, Philippines. The results of the needs assessment underscored the importance of developing a CCTV camera placement plan for the barangay. The researcher proposed to develop a plan that aims to provide measures to improve safety and security within the community. Based on the needs assessment that has been conducted, several recommendations were drawn. Firstly, it was strongly advised to design a CCTV camera placement plan in the barangay. A follow-up study may be conducted focusing on this aspect. Future researchers must strategically place the CCTV in the area to optimize its full potential for securing the community. Secondly, community engagement and collaboration were highlighted as crucial factors for successful implementation, emphasizing the importance of involving community members, stakeholders, and educational institutions in the planning process. Thus, when designing a strategic CCTV placement plan, the involvement of various stakeholders is highly encouraged. Further, allocating resources for installation, maintenance, and monitoring was also proposed to ensure the sustainability and effectiveness of the surveillance system. Lastly, continuous evaluation and improvement of the CCTV camera placement plan when implemented is highly recommended, emphasizing the need for regular reviews, resident feedback, and performance monitoring to optimize the system's functionality. These recommendations provide valuable guidance for barangay officials in their pursuit of enhanced safety and security. By implementing the proposed plan that may be developed through this study and considering the input of the community, the barangay can create a safer environment and promote a sense of security among its residents.

SCMR expert consensus statement for cardiovascular magnetic resonance of patients with a cardiac implantable electronic device

Cardiovascular magnetic resonance (CMR) is a proven imaging modality for informing diagnosis and prognosis, guiding therapeutic decisions, and risk stratifying surgical intervention. Patients with a cardiac implantable electronic device (CIED) would be expected to derive particular benefit from CMR given high prevalence of cardiomyopathy and arrhythmia. While several guidelines have been published over the last 16 years, it is important to recognize that both the CIED and CMR technologies, as well as our knowledge in MR safety, have evolved rapidly during that period. Given increasing utilization of CIED over the past decades, there is an unmet need to establish a consensus statement that integrates latest evidence concerning MR safety and CIED and CMR technologies. While experienced centers currently perform CMR in CIED patients, broad availability of CMR in this population is lacking, partially due to limited availability of resources for programming devices and appropriate monitoring, but also related to knowledge gaps regarding the risk-benefit ratio of CMR in this growing population. To address the knowledge gaps, this SCMR Expert Consensus Statement integrates consensus guidelines, primary data, and opinions from experts across disparate fields towards the shared goal of informing evidenced-based decision-making regarding the risk-benefit ratio of CMR for patients with CIEDs.

DNA Barcoding of Catfishes (Order: Siluriformes) with New Records of Two Species from Eastern Nepal

The freshwater bodies of Nepal host a great deal of fish diversity; however, the molecular study of Nepalese fish is still in its early stages. Conservation management tactics require knowledge of the real species composition, often impeded by descriptions of intermittent species based on traditional taxonomy. Catfish, one of the most overfished taxa on the planet, are abundant and heavily exploited in the eastern region of Nepal. Hence, actual catfish diversity in this region needs to be examined using a combined morphological and molecular DNA barcoding approach. In this study, we sequenced the cytochrome oxidase subunit I (COI) gene in Nepalese fish species for the first time and used it for molecular identification. Altogether, 99 specimens representing 29 species belonging to 21 genera and 8 families were successfully barcoded. They were found to be 98.5–100% identical to the known sequences deposited in the GenBank and BOLD databases. Of these, two species, Amblyceps arunachalense and Erethistoides sicula, were recorded for the first time in Nepal. Out of 29 species, one species was found to be Endangered, one species under Vulnerable, two species under Near Threatened, one species under Data Deficient, and 24 species under Least Concern. The intraspecific genetic distances within species ranged from 0 to 5%. The highest intraspecific genetic distances (Kimura 2‐parameter) were found among the individuals of two species, namely, E. sicula (4%) and Glyptothorax telchitta (5%), indicating the presence of putative (sub)species. The interspecific genetic distances among the catfishes in eastern Nepal ranged between 8.47% (between Glyptothorax trilineatus and G. cavia) and 26.38% (between Amblyceps arunachalense and Chaca chaca). The GC content at the 1st, 2nd, and 3rd positions of the codons was found to be 42.4%, 49.3%, and 43.8%, respectively. These findings will support future initiatives for fish resource inventory, monitoring, and management. It is also an important input to the DNA barcode library of catfish in the eastern region of Nepal.

Providing a Regional Policy-Making Ecosystem Model for the Ministry of Health and Medical Education of Iran

Objective: The purpose of this study was to provide a regional policy-making ecosystem model for the Ministry of Health and Medical Education of Iran. Methodology: The research method was descriptive-analytical, with an applied nature. The statistical population of this study consisted of experts in the Ministry of Health and Medical Education. Considering the type of research, 20 individuals with master's and doctoral degrees and more than five years of experience in this field were purposefully sampled and selected. Data collection was conducted using field methods, including interviews and questionnaires. The obtained data were analyzed using interpretive structural modeling. Findings: The findings indicated that 12 factors were identified as part of the regional policy-making ecosystem for the Ministry of Health and Medical Education of Iran. The (process value network) was identified as the most influential component of the regional policy-making ecosystem for the Ministry of Health and Medical Education of Iran. Following this, the factors of (sustainable development) were identified, with (resource management and monitoring and evaluation) in the third level, (current situation analysis) at the second level, and finally (coordination and cooperation, infrastructure and technology, public participation, international cooperation, national policies, and process achievements) occupying the first level. Conclusion: Therefore, it can be concluded that these factors influencing the regional policy-making ecosystem for the Ministry of Health and Medical Education of Iran may lead to further development and success of this organization

A Hybrid convolution neural network for the classification of tree species using hyperspectral imagery.

In recent years, the advancement of hyperspectral remote sensing technology has greatly enhanced the detailed mapping of tree species. Nevertheless, delving deep into the significance of hyperspectral remote sensing data features for tree species recognition remains a challenging endeavor. The method of Hybrid-CS was proposed to addresses this challenge by synergizing the strengths of both deep learning and traditional learning techniques. Initially, we extract comprehensive correlation structures and spectral features. Subsequently, a hybrid approach, combining correlation-based feature selection with an optimized recursive feature elimination algorithm, identifies the most valuable feature set. We leverage the Support Vector Machine algorithm to evaluate feature importance and perform classification. Through rigorous experimentation, we evaluate the robustness of hyperspectral image-derived features and compare our method with other state-of-the-art classification methods. The results demonstrate: (1) Superior classification accuracy compared to traditional machine learning methods (e.g., SVM, RF) and advanced deep learning approaches on the tree species dataset. (2) Enhanced classification accuracy achieved by incorporating SVM and CNN information, particularly with the integration of attention mechanisms into the network architecture. Additionally, the classification performance of a two-branch network surpasses that of a single-branch network. (3) Consistent high accuracy across different proportions of training samples, indicating the stability and robustness of the method. This study underscores the potential of hyperspectral images and our proposed methodology for achieving precise tree species classification, thus holding significant promise for applications in forest resource management and monitoring.

SMART CLOUD BASED ECOLOGICAL SYSTEM FOR CONTACTLESS VEHICLE CLEANING

The rise in the overall standard of living leads to an increase in the number of used cars. As the number of cars increases, so do the maintenance requirements. As a result, the growth of vehicle washes is increasing. However, the issue of their economy comes up. The current literature sources present the following ecological and technical issue: how to determine and apply the best use of water and detergent on automated car washing systems while minimizing vehicle washing time.Thus, this paper tries to propose a ecological contactless vehicle washing smart system based on the application of cameras, programabile logilac units and cloud databses for high-quality vehicle washing, monitoring and optimal resources usage.Specifically, the proposed smart system for automatic contactless vehicle washing could be used for water flow regulation, detergent concentration regulation and for managing the process of determining the overall dimensions of the vehicle.

Self-Adaptive Edge Computing Architecture for Livestock Management: Leveraging IoT, AI, and a Dynamic Software Ecosystem

The agricultural industry is encountering exceptional difficulties due to shifts in the macroeconomic landscape, and the prospects of the livestock sub-sector could be more precise. The elimination of subsidy payments due to agricultural policy changes resulting from Brexit poses a significant threat to farmers’ financial stability and overall well-being, jeopardizing their enterprises and lives. Farmers must pursue adaptive tactics to endure the consequences of evolving socio-political situations. This research investigates the capabilities of Dynamic Software Ecosystem (DSE) as an analytical tool in the context of managing livestock within the farming sub-sector. In Smart Farming, using the Internet of Things (IoT) and Blockchain (BC) facilitates the monitoring of resources and ensures traceability across the value chain. This enables farmers to enhance their operational efficiency, disclose the source of their agricultural products, and assure customers about the output’s caliber. This study introduces a platform that utilizes the IoT, Edge Computing, Artificial Intelligence (AI), and BC in Smart Farming settings. The Optimised Live Stock Management System (OLSMS) employs the Edge Computing Design to enable real-time monitoring of dairy animals and feed grain conditions. It guarantees the reliability and long-term viability of various production procedures. The efficiency of the Expert System is shown by its dependability rate of 92.3%, as determined by comparing its outcomes with those of a group of experts in raising livestock. The experimentation conducted on various scenarios has shown intriguing findings on implementing effective livestock management methods within certain environmental variables, such as weather and precipitation.

Optimizing water quality classification using random forest and machine learning

Water is the most precious and essential resource among all natural resources. With the increase in industrialization and human activities over recent decades, the state of water resources has been significantly impacted. Effective water quality monitoring has become a priority for cities worldwide. Modern technologies such as cloud computing, artificial intelligence, remote sensing, and the Internet of Things provide new opportunities to enhance water resource monitoring systems. This paper explores the application of the random forest model for water quality classification based on chemical attributes. The study includes three experiments: using the full set of features, excluding the pH feature, and using only the top three significant features. The random forest model trained on the full dataset achieved 100% accuracy. When the pH feature was excluded, the model maintained an accuracy of 76%, highlighting the importance of this feature but also showing the potential for compensation by other parameters. Using only the top three significant features (pH, conductivity, and nitrate), the model again achieved 100% accuracy. The results demonstrate that feature optimization without significant loss of model accuracy is a promising approach to improve water quality monitoring and assessment processes. This approach allows for reduced data collection time and costs while maintaining high predictive accuracy. The findings confirm that machine learning, particularly random forest models, can be effectively used for water quality classification, ultimately supporting better management and conservation of water resources.

Development and applications of an integrated space-air-ground observation network in natural resource monitoring and supervision

Timely and accurate monitoring is a prerequisite to survey the types, quantities, quality, and distribution of various natural resources. Currently, satellite remote sensing is the major observation method, which has advantages in observation scale, fast speed, and low cost. However, with the increasingly precise management of natural resource, satellite remote sensing faces some shortcomings in observation timeliness, dynamism, and accuracy. To solve these problems, combining space-based, air-based, and ground-based observation technologies can offer an effective approach by taking the advantages of each technology. This study focuses on development and applications of an integrated space-air-ground observation network to avoid the insufficiencies of individual monitoring method in natural resource monitoring and supervision. In this paper, we combined satellite remote sensing, drone photography, video surveillance, and field survey to establish an integrated space-air-ground observation network, proposed a cooperative observation mechanism in observation task, scale, and time. Then monitoring indicators and supervision process was established via indicator library and workflow engine, realizing closed-loop management of “discovery, analysis, verification, disposal, and cancellation” for natural resource monitoring and supervision. Afterward, by connecting the observation network and following the closed-loop management process, a cross terminal software was designed and developed to achieve process automation of natural resource monitoring and supervision. Finally, the observation network and software was put into practice, and the results indicate that the integrated space-air-ground observation network can effectively improve the efficiency and accuracy of natural resource of monitoring and supervision.

Status Analysis of Radar Technology in Forest and Grass Resources Monitoring Based on Bibliometrics

Status Analysis of Radar Technology in Forest and Grass Resources Monitoring Based on Bibliometrics

Predictive Monitoring of Resources Consumption in Project Management

Monitoring resource consumption is a critical concern in project management, as it can significantly impact a project’s success. Project management experts often rely on their experience and heuristics to navigate management challenges and adhere to predefined constraints. However, relying solely on experts’ judgments can lead to disagreements and biases, hindering consensus and optimal decision-making. In this context, a data-driven approach leverages accumulated data and machine learning to develop unbiased models suitable for automation, including prediction, classification, anomaly detection, and more. In this paper, we propose a method for predicting resource consumption, encompassing expected, unplanned, and surpassing tasks. Our experiments demonstrate strong predictive performance using real-world datasets across various task types.

2000–2019年呼伦湖透明度卫星遥感数据集

Water clarity is a significant parameter for evaluating the water quality of lakes. Monitoring the long-term temporal and spatial changes of water clarity of lakes can provides valuable insights for evaluating water quality and eutrophication status of water bodies, as well as guiding lake environmental management and ecological restoration. With MODIS Terra satellite images, we excluded the influence of cloud cover and other interference factors to evaluate the water clarity (i.e. Secchi disk depth), and finally produced a dataset of water clarity of Hulun Lake from 2000 to 2019. It has been validated that the coefficient of determination of the dataset is 0.8, and the root mean squared error is 21.27cm, indicating its accuracy in meeting the monitoring requirements. This data set is expected to serve as a valuable resource for remote sensing-based water quality monitoring and environmental governance of Hulun Lake at a scale of long time series.

К РАСЧЕТАМ АНТРОПОГЕННЫХ ВЫБРОСОВ ИЗ ИСТОЧНИКОВ И АБСОРБЦИЙ ПОГЛОТИТЕТЯМИ ПАРНИКОВЫХ ГАЗОВ В ЛЕСНОМ И СЕЛЬСКОМ ХОЗЯЙСТВЕ ДЛЯ ЕЖЕГОДНОГО НАЦИОНАЛЬНОГО ДОКЛАДА РЕСПУБЛИКИ КАЗАХСТА

The results presented in the article were obtained in the process of preparing the National Report on the inventory of anthropogenic emissions from sources and absorption of greenhouse gases not regulated by the Montreal Protocol, in terms of land use. The report is submitted annually by the Republic of Kazakhstan, as a party to the United Nations Framework Convention on Climate Change (UNFCCC). Preliminary calculations of the dynamics of carbon dioxide (CO2) associated with land use in the Republic of Kazakhstan for 1991...2020 showed that its absorption from the atmosphere by natural ecosystems could range from 3 to 50...60 million tons per year, and emissions into the atmosphere – from 10 to 45 million tons/year. In the process of research, a detailed analysis of the country's existing system of ground-based monitoring of land use and land resources was carried out with calculations of anthropogenic CO2 flows at various territorial levels. The results obtained confirm the possibility of calculating greenhouse gases at the zonal and regional levels. This confirms the possibility of additional control of calculations of greenhouse gas fluxes associated with land use and assessment of the potential for a possible increase in absorption volumes for natural ecosystems (Forests and Pastures) and reductions in emissions for the Croplands agroecosystem.

Cross­Media Platform as a Tool for Promoting the Cultural Heritage of the Ukrainian Diaspora in the Conditions of Development of a Digital Society

The relevance of the research topic is determined by the socio-cultural processes in modern Ukraine. Therefore, the study and popularization of the cultural heritage of the Ukrainian diaspora among the youth with the help of information and communication technologies during the development of a digital society becomes especially relevant.
 The purpose of the work is to use a cross-media platform as an application in information and communication technologies to popularize the cultural heritage of the Ukrainian diaspora under the conditions of a digital society formation.
 The research methodology is based on the application of general scientific and special research methods. In particular, the method of historical and source research, analysis of scientific literature, methods of analysis and synthesis, content analysis, comparative and analytical monitoring of Internet resources, as well as the “Tree of Goals” method were used.
 The results. As a result of scientific research, a cross-media platform project was implemented as a means of popularizing the cultural heritage of the Ukrainian diaspora using a virtual exhibition in the form of a website, a Telegram channel, and an Instagram page. The main stages of the product creation were described, the approbation of the project was carried out and its possibilities as a tool for spreading knowledge about the cultural heritage of the Ukrainian diaspora were determined.
 The scientific novelty of the obtained results lies in the fact that the process of representation and popularization of the cultural heritage of the Ukrainian diaspora using a cross-media platform as a means of educational activity under the conditions of a digital society formation, was for the first time clarified.
 The practical significance. The practical significance of the results of the work is that the conducted research will allow teachers to increase student/pupil interest in the cultural heritage of the Ukrainian diaspora in thematic courses, allow implementation of projects using a cross-media platform, and provide students/pupils an additional platform for studying this material or representing their creative projects.
 Conclusions. It is established that a cross-media platform is a method of communication that involves a dialogue with the audience through the use of multimedia and various platforms for communication.