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Author: Andrej Simonovic

  • TECHNOLOGICAL BASIS OF “INDUSTRY 4.0”

    Impact of Industry 4.0 on agricultural industry

    • Andrej Simonović
    • Dragan Marković
    • Vojislav Simonović
    • Dragan Krstić
    Industry 4.0, Vol. 5 (2020), Issue 4, pg(s) 164-166
    • Abstract
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    Industry 4.0 represents the newest generation of industry development. Every day the various demands in industry are getting more and more demanding. The demand for shorter production and delivery time, more efficient and automated processes has led us to the Industry 4.0. It is necessary to include and integrate the latest developments based on digital technologies as well as the interoperability process across them. The goals is to enable companies to transmit information in real time in terms of performance and behaviour. Industry 4.0 can be applied to any branch of industry. Agricultural industry is no exception. As far as agricultural machinery is concerned, it is a very important part of agricultural industry. Agricultural machinery incorporates electronic controls and it is a part of digital age, enhancing their current performance. In addition to the electronics, using sensors and drones, supports the data collection of several agriculture key aspects, such as weather, animals and crops behaviour, geographical spatialization, etc. The main tasks are how to apply the right methods and methodologies in order to support a better supply chain decision-making process, how to automate the process and how can Industry 4.0 help a person, who is in agricultural industry, in order to make effective decisions based on objective data.

  • MECHANIZATION IN AGRICULTURE

    Correlation of light wavelengths on spectral cameras and vegetation indexes in barley crop scouting

    • Vojislav D. Simonovic
    • Andrej Simonovic
    • Dragan D. Marković
    • Dragan Krstić
    • Ivana M. Medojević
    • Ivan J. Zlatanović
    Mechanization in agriculture & Conserving of the resources, Vol. 66 (2020), Issue 2, pg(s) 68-70
    • Abstract
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    •  Article PDF

    This paper presents a case study of a barley field experiment that was periodically scouted using a drone spectral camera. The camera has 4 bands so barley was scouted using 4 wavelengths of light – Green, Red, Red Edge and Nir Infra Red (NIR). Based on these wavelengths it is possible to calculate different vegetation indexes known in science and practice. In this paper, 15 such indices were used. The research work concerned the observation of correlation between individual wavelengths and corresponding vegetation indexes. This paper seeks to emphasize the importance of particular wavelengths and spectral areas in crop scouting

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