The concept of automated environmental monitoring intellectual system based on compact autonomous robots

 Y.E. Shishkin1,2, A.N. Grekov1

 1 Institute of Natural and Technical Systems, Russian Federation, Sevastopol, Lenin St., 28

2 Federal State Educational Institution of Higher Education «Sevastopol State University», Russian Federation, Sevastopol, Universitetskaya St., 33


DOI: 10.33075/2220-5861-2018-4-63-69

UDC 004.9:004.41


     This article proposes an intelligent system concept for automatic monitoring of the aquatic environment main parameters, in order to detect their anomalies and assess quantitative and qualitative indicators, including the determination of spatial and temporal characteristics of the field under study. The system is built on the basis of a network of small autonomous surface robots. A conceptual model of the monitoring system for implementation of automated integrated monitoring of the environment parameters throughout the entire observation field is proposed.

     A software model has been developed and simulation experiments have been conducted to calculate the main indicators and assess environment spatial and temporal variability. According to the results of the simulation, control maps of the stations optimal density were formed. The proposed approach to solving the problem of monitoring the aquatic environment in comparison with the traditional has such advantages as scalability, flexibility, speed of deployment and clotting, self-organization, the ability to create a wide field of view by changing the number of robots.

     The work of the algorithm for obtaining maps of optimal intervals on the stations grid where measurements of the aquatic environment parameters are made has been experimentally tested using the example of constructing a dissolved oxygen heat map in the surface layer of the bay of Sevastopol. This can serve as confirmation of its validity as information support for an intelligent decision-making support system in the organization of the optimal station location process.

     The proposed model was developed for the use in decision support systems for continuous automated control of the monitoring process by autonomous surface robots without operator participation, solving the problem of minimizing the time of taking field parameters and increasing autonomy by building an energy efficient route. The use of systematic data collection will provide fundamentally new scientific results at minimum cost.

Keywords: monitoring, detection of anomalies, environmental monitoring system, mathematical modeling, Big Data, cloud computing, clustering, critical systems, data mining.

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