Object: processes of the decision support in the development and implementation of a surface water monitoring system based on the Internet of Things; objective: to increase the efficiency of decision-making processes related to the development and implementation of surface water monitoring system through the development and integration of models, methods and information technology based on the Internet of Things; methods: set theory, graph theory, matrix theory, submodularity principle, greedy heuristics, annealing simulation method, entropy maximization, Voronoi diagram, Delaunay triangulation - for placement of sensors and IoT devices in the monitoring system; probability theory, methods of descriptive statistics, variational calculations, correlation analysis - for the methodology of long-term data processing and analysis of water quality; principal components method, factor analysis - to determine a set of sensors in IoT water quality control devices; SCAI-graph, mashup methodology, prototyping technologies, compression measurement models - when creating information technology for designing surface water monitoring systems based on IoT; novelty: a new method of sensor placement is proposed, which, unlike the known ones, combines entropy-based placement technology with the procedure of efficient sensor reuse and allows to take into account the parameters of location depth, the method is based on greedy search heuristics, which uses the properties of entropy in terms of maximum, subadity and ambiguity, with entropy being defined as the ratio of the length of the probe to the length of the watercourse and maximized to the network level; the model of the IoT sensor network has been improved, due to the component of taking into account the depth of immersion of IoT devices, which allows to take into account the presence of underwater nodes and determine the location of surface and underwater nodes; further developed data processing technology based on automatic feature extraction using the principal component analysis to solve the problem of determining the types of sensors used in water quality control devices IoT, which allows you to reasonably choose parameters that can detect changes in water quality by a limited number of sensors; the methodology of processing long-term statistical data of surface water quality analysis has been improved by systematizing the processes of complex analysis and forecasting, which allows to formulate and implement a systematic approach to assessing the dependences and mutual influence of reservoir quality indicators and factors characteristic of the study area reservoirs and factors characteristic of the study area, and to predict changes in hydrochemical parameters of water in the long run; gained further development IoT-based surface water monitoring technology design has been further developed through the adaptation of SCAI technology and mash methodology to the objectives of the subject area, which allows to increase the validity of decisions on creating a basic configuration of the IoT system, starting from the value proposition, which is especially important. for experts in subject areas not related to information and communication technologies; research results: new models, methods and appropriate software have been developed, which create applied information technology for the development and implementation of IoT monitoring systems of water bodies, and will allow in practice, added confirmations of relevant implementations, to monitor surface water in real time, using the proposed decision support processes to organize the system of monitoring, transmission, storage and processing of data using IoT, to better understand the sources of various water pollutants, the consequences of water control policies and the impact of various substances in water sources; the branch: information technology.
