The paper presents a new approach to solving the problem of water quality control in rivers. We proposed an intelligent system that monitors and controls the quality of water in a river. The distributed measuring system works with a central control system that uses the intelligent analytical computing system. The Biochemical Oxygen Demand (BOD) and Dissolved Oxygens (DO) index was used to assess the state of water quality. Because the results for the DO measurement are immediate, while the measurement of the BOD parameter is performed in a laboratory environment over a period of several days, we used Artificial Neural Networks (ANN) for immediate estimation BOD to overcome the problem of controlling river water quality in real time. Mathematical models of varying complexity that represent indicators of water quality in the form of BOD and DO were presented and described with ordinary and distributed-parameters differential equations. The two-layered feed-forward neural network learned with supervised strategy has been tasked with estimating the BOD state coordinate. Using classic ANN properties, the difficult-to-measure river ecological state parameters interpolation effect was achieved. The quality of the estimation obtained in this way was compared to the quality of the estimation obtained using the Kalman–Bucy filter. Based on the results of simulation studies obtained, it was proved that it is possible to control river aeration based on the measurements of particular state coordinates and the use of an intelligent module that completes the “knowledge” concerning unmeasured data. The presented models can be further applied to describe other cascade objects.

This paper presents a vision system that measures the position of an aircraft relative to the runway (RWY) during a landing approach. It was assumed that all the information necessary for a correct approach was based entirely on an analysis of the image of the runway and its surroundings. It was assumed that the way the algorithm works, as well as possible, should imitate the pilot’s perception of the runway. Taking into account the above and the fact that the infrastructure at each airport is different, it has been decided to use artificial neural networks with a dedicated learning process for any airport, based on the simulation environments. Such an action will enable the generation of a synthetic video sequence without the need for costly and time-consuming flights. The presented solution was tested in real flight conditions on an experimental aircraft, and the selected test results are presented in this article.

The waters of rivers are not only used for consumption, industry and agriculture but have also found their way into the transport and energy generation sectors. Many disturbances introduced into the aquatic environment are of the natural variety, which are the result of “admixtures” contained in water, e.g., through contact with soil, and of man-made types, which are directly related to humanities destructive influences. In the presented examinations, the most important processes affecting the spread and transport of these pollutants are taken into account, i.e., advection and diffusion. The authors present observations on the influence of the diffusion phenomenon on river flow modelling processes. Such an approach allows for the separation of the dynamics of water flow and the dynamics of transport of the dissolved substance mass. Specifically, phenomena occurring in relation to spatial coordinates, time and variable parameter values in the proposed mathematical model were analysed. Ultimately, this research will contribute to the correct design and implementation of a complementary diffusion module as an extension to an intelligent water quality control and monitoring system. The Intelligent Analytical Computing Control System architecture under development already includes other modules such as the Intelligent Filtration and Prediction Module and, complemented by the Intelligent Diffusion Module, provides a complementary tool for monitoring river hydromorphology. Implementation of the above solution will help to improve water quality, thus preventing and eliminating the appearance of undesirable pollutants in rivers, and increase the standard of living in the current threatened environmental world.