The use of artificial intelligence technologies as an element of improving the methodology of environmental monitoring of the Black Sea

Abstract

This article is devoted to the results of an experimental study, the purpose of which was to evaluate the possibility of using artificial intelligence technologies to improve the methodology of environmental monitoring of the Black Sea using the computer vision model (YOLO). The basis of environmental monitoring of water bodies is the determination of pollution, the saprobic index was chosen as its quantitative characteristic in this study. Saprobity is characterized by the degree of contamination of the reservoir with organic substances and their decomposition products. It is determined by the species composition of organisms (saprobionts) living in water and their number (frequency of occurrence). Microalgae of periphyton, which serve as indicators for the presence of organic substances, were selected as saprobionts. The composition and quantity of microalgae involved in the microfouling process were determined using the “fouling glasses” method by installing glasses in the coastal water area under study. The identification and calculation of the frequency of occurrence of microalgae present at a certain point in time in the water area was carried out by microscopy of microfouling samples. A certain composition of microalgae made it possible to calculate the saprobic index of the studied water body and draw a conclusion about its contamination. This method requires the participation of highly qualified specialists and the time required to process the microscopy results. In this regard, artificial intelligence technologies were used to accelerate the process as an element of improving the methodology of environmental monitoring of the Black Sea area. The use of the computer vision (YOLO) model made it possible to reduce the study time and assess the quality of the water body, which confirmed the effectiveness of the proposed technology in order to improve environmental monitoring of water bodies.