Wyniki wyszukiwania - BazTech

1

Crowd Size Estimation and Detecting Social Distancing using Raspberry Pi and OpenCV

Milton Davidson Kamala Dhas, Velraj Arun Ra

International Journal of Electronics and Telecommunications

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2023

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Vol. 69, No. 1

19--24

EN

In this covid19 pandemic the number of people gathering at public places and festivals are restricted and maintaining social distancing is practiced throughout the world. Managing the crowd is always a challenging task. It requires monitoring technology. In this paper, we develop a device that detects and provide human count and detects people who are not maintaining social distancing. The work depicted above was finished using a Raspberry Pi 3 board with OpenCV-Python. This method can effectively manage crowds.

2

Application of the OpenCV library in indoor hydroponic plantations for automatic height assessment of plants

Pietrzykowski Sławomir Krzysztof, Wymysłowski Artur

Journal of Automation Mobile Robotics and Intelligent Systems

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2022

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Vol. 16, No. 2

55--63

EN

This paper presents a method for automatically measuring plants’ heights in indoor hydroponic plantations using the OpenCV library and the Python programming language. Using the elaborated algorithm and Raspberry Pi-driven system with an external camera, the growth process of multiple pak choi cabbages (Brassica rapa L. subsp. Chinensis) was observed. The main aim and novelty of the presented research is the elaborated algorithm, which allows for observing the plants’ height in hydroponic stations, where reflective foil is used. Based on the pictures of the hydroponic plantation, the bases of the plants, their reflections, and plants themselves were separated. Finally, the algorithm was used for estimating the plants’ heights. The achieved results were then compared to the results obtained manually. With the help of a ML (Machine Learning) approach, the algorithm will be used in future research to optimize the plants’ growth in indoor hydroponic plantations.

3

Application of visual system for hand control of 3D manipulator

Milecki A., Sawicki Ł.

Archives of Mechanical Technology and Materials

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2015

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Vol. 35

92--100

EN

The article concerns controlling of a 3-axles manipulator by hand movement, recognized by visual system. In the investigations the Kinect sensor was used, which enabled the acquiring of 2D hand images with depth parameter. The OpenCV library was used for recognition of hand position in a real-time computer based control system. The control program was written in C++ language, which allows the processing of 15 frames per second. The proposed control system enabled to operate the manipulator with the same frequency.

PL

Artykuł skupia się na sterowaniu 3 osiowego manipulatora wykorzystując obraz głębi pozyskany z sensora Kinect oraz bibliotekę OpenCV, przeznaczoną głównie do obróbki obrazu w czasie rzeczywistym. Opracowany program został napisany w C++ i pozwala na operowanie manipulatorem z prędkością 15 FPS. Komunikacja ze sterownikiem manipulatora została zapewnioną za pomocą kabla USB.