The given article considers results of experimental measurements, productivity comparison and master controller executive system of flat-plate solar collector with thermosiphon circulation and flat solar collector with special chemical coating. There has been developed master controllers control module, which receives data from temperature and lighting sensors, obtained in operation process. The aim of the research is getting the solar collectors? optimal parameters, representing maximal usage performance index, controllability, as well as, construction type, allowing energy saving. In the recent years flat-plate solar collectors with chemical coating are characterized with higher efficiency in real conditions usage. The developed master controllers? executive system is used for monitoring the installation?s main parameters, as well, it permits to compare characteristics of solar collector with thermosiphon circulation to those of flat-plate solar collector with chemical coating. The obtained experimental data has shown, that flat solar collectors, using chemical coating as a transfer medium in solar heat supply system, have an advantage in the context of usage effectiveness. The heat output and water heating in a flat solar collector are calculated, which vary depending on the intensity of solar radiation. The thermal efficiency of a flat solar collector with a thermosiphon tank based on the Mojo V3 platform using Dallas sensors is calculated.

This article analyzes the most famous sign languages, the correlation of sign languages, and also considers the development of a verbal robot hand gesture recognition system in relation to the Kazakh language. The proposed system contains a touch sensor, in which the contact of the electrical property of the user's skin is measured, which provides more accurate information for simulating and indicating the gestures of the robot hand. Within the framework of the system, the speed and accuracy of recognition of each gesture of the verbal robot are calculated. The average recognition accuracy was over 98%. The detection time was 3ms on a 1.9 GHz Jetson Nano processor, which is enough to create a robot showing natural language gestures. A complete fingerprint of the Kazakh sign language for a verbal robot is also proposed. To improve the quality of gesture recognition, a machine learning method was used. The operability of the developed technique for recognizing gestures by a verbal robot was tested, and on the basis of computational experiments, the effectiveness of algorithms and software for responding to a verbal robot to a voice command was evaluated based on automatic recognition of a multilingual human voice. Thus, we can assume that the authors have proposed an intelligent verbal complex implemented in Python with the CMUSphinx communication module and the PyOpenGL graphical command execution simulator. Robot manipulation module based on 3D modeling from ABB.

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