Abstract
The management of unmanned technology is becoming increasingly important in various fields, including the aviation industry, geodesy, the agricultural sector, and many others. To ensure efficient and safe management, most robots require the use of various remote-control systems, which can be complex and overly costly. However, the Cascade DataHub method offers a new approach to organizing the management of unmanned technology, based on integrating real-time data from various sources into a single platform. This method provides fast and convenient access to important data for decision-making, improves the accuracy and efficiency of unmanned aerial vehicle management, and reduces remote control costs. In this article, we will delve deeper into the Cascade DataHub method and its application for organizing work management, as well as analyse its advantages and disadvantages.
The Cascade DataHub method allows for creating a unified platform for collecting, processing, and analysing data from unmanned aerial vehicles. This method enables the integration of various data sources, such as GPS, cameras, sensors, other control, and monitoring systems, into a unified system that allows monitoring, analysis, and real-time management of the devices.
The key feature of the method is the ability to create various connections between data, allowing the analysis and control of robots from different perspectives. Thanks to real-time data processing technology, operators can instantly respond to dangerous situations, enhancing the safety and reliability of management.
Furthermore, the Cascade DataHub method helps reduce drone management costs by enabling control and monitoring of agents remotely from a convenient location, reducing the need for a large amount of specialized equipment and personnel.
Despite the advantages of the Cascade DataHub method, it also has its drawbacks. One of the biggest drawbacks is the need for high-speed internet connection to transmit a large amount of data in real-time. There may also be issues with system stability in unforeseen situations, such as the disconnection of one of the data sources.
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Kalashnikova, V., Binko, I., Kovalevskyi, M., Pyvovar, M., Shevel, V. (2024). Approaches to Structuring Control in an Automated Mobile System. In: Nechyporuk, M., Pavlikov, V., Krytskyi, D. (eds) Integrated Computer Technologies in Mechanical Engineering - 2023. ICTM 2023. Lecture Notes in Networks and Systems, vol 996. Springer, Cham. https://doi.org/10.1007/978-3-031-60549-9_38
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