Advances In Cyber-Physical Systems

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Author: search.filters.author.Kushnir, Dmytro

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    Microprocessor subsystem of the smart house to control the multichannel irrigation of the room plants
    (Видавництво Львівської політехніки, 2022-06-06) Borak, Taras; Kushnir, Dmytro; Paramud, Yaroslav; Lviv Polytechnic National University
    This article develops the principles of building an intelligent home microprocessor subsystem to control the multi-channel irrigation of houseplants. The relevance of this topic has also been substantiated. Currently, there is a small number of devices in demand with a comfortable user interface and timer, which allows to adjust the watering at any time of day. The advantages over other available analogs and the need to create a customized system have been investigated. The developed structuralschematic diagram of the irrigation control system of houseplants based on the Arduino Nano microcontroller and a diagram of the algorithm of the subsystem has been proposed and given. As a result, there has been an example of the development of a subsystem that aims to improve and simplify the care of houseplants, which will save time and water resources.
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    The algorithm of cyber-physical system targeting on a movable object using the smart sensor unit
    (Lviv Politechnic Publishing House, 2020) Kushnir, Dmytro; Paramud, Yaroslav; Lviv Polytechnic National University
    It is known that smart sensor units are one of the main components of the cyber-physical system. One of the tasks, which have been entrusted to such units, are targeting and tracking of movable objects. The algorithm of targeting on such objects using observation equipment has been considered. This algorithm is able to continuously monitor observation results, predict the direction with the highest probability of movement and form a set of commands to maximize the approximation of a moving object to the center of an information frame. The algorithm has been verified on an experimental physical model using a drone. The object recognition module has been developed using YOLOv3 architecture. iOS application has been developed in order to communicate with the drone through WIFI hotspot using UDP commands. Advanced filters have been added to increase the quality of recognition results. The results of experimental research on the mobile platform confirmed the functioning of the targeting algorithm in real-time.