Andrzej Borusiewicz, Krzysztof Kapela, Paulina Drożyner and Tomasz Marczuk
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Martin Ingeli, Jana Galambošová, Miroslav Macák and Vladimír Rataj
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Raimondo Gallo, Giovanni Carabin, Renato Vidoni, Pasqualina Sacco and Fabrizio Mazzetto
systems able to operate following PrecisionAgriculture and Precision Forestry approaches for agroforestry companies. Indeed, each of those applications should be supported by a technological platform that has the ability to perform the collection, the processing, the analysis, and the evaluation of the raw data, as well as the use of the obtained information, in a sequential and integrated way. To ensure the management and the processing of all these functions, the platform must be supported by adequate information system with the capability to satisfy the specific
This paper presents a review on current and emerging application possibilities for unmanned aerial vehicles (UAVs). The introduction section of the paper briefly describes some of the application areas in which drones are currently being used. The next chapters of the paper describe more detailly the use of UAVs for aerial photography, filming, security and logistics, GIS, land and water surveys. The main focus of the last chapters is on the advantages and the disadvantages of the drones usage in precision agriculture, wildlife and nature observations and archaeology. The last chapters also provide information on how the advanced information technology solutions can be implemented in order to provide means for fighting invasive species, to increase the yield of certain crops, to monitor and predict flooding, wildfires and other disasters, etc. This paper provides only overview of the most interesting and widely available applications of the UAVs, but there are also many other more specific and dedicated solutions for implementation of the drones for different purposes.
Vojtěch Lukas, Fernando Rodriguez-Moreno, Tamara Dryšlová and Lubomír Neudert
estimating nitrogen concentration of winter wheat at different growth stages. In PrecisionAgriculture , vol. 11 , no. 4, pp. 335‒357. DOI: 10.1007/s11119-010-9165-6.
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Viliam Nagy, Gábor Milics, Norbert Smuk, Attila József Kovács, István Balla, Márton Jolánkai, József Deákvári, Kornél D. Szalay, László Fenyvesi, Vlasta Štekauerová, Zoltán Wilhelm, Kálmán Rajkai, Tamás Németh and Miklós Neményi
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A. Tzounis, N. Katsoulas, K.P. Ferentinos, T. Bartzanas and C. Kittas
Precision greenhouse agriculture requires several measuring points in order to have a better overview of the whole cultivation area. Climate variability within the covered area of a greenhouse can result in a non-uniform plant development and reduced productivity. Therefore, a distributed system, capable of taking multi-point measurements would be able to catch the climatic gradients in order to provide growers with a more detailed depiction of the climate at any time and early warnings of potential threats. Furthermore, the distributed monitoring can offer the appropriate inputs to more sophisticated distributed or plant-based climate control algorithms. The significant price drop in embedded computer and wireless communication chips, as well as the overall maturity of the available, low-power platforms have made the deployment of Wireless Sensor Networks increasingly attractive in modern agricultural facilities. This paper presents a Wireless Sensor Network (WSN) deployed for long periods in commercial facilities, equipped with shading screens and cooling pads placed in different directions, namely vertically to the plantation and parallel to it. The evolution of the various climate parameters in both greenhouses and the effect of the climate on the plants and the wireless communications are analyzed and presented.
In the last decade, the rate of the industrial usage of fixed-wing and blended wing aircraft has increased. A 1–2-km2 area can be surveyed by such a drone within 30 to 60 minutes, without any special infrastructure, and this can be repeated at any time. This provides an opportunity to conduct automatized surveys and time series data testing, which can be used as a basis to decide specific processes. The state and the development of the plants can be monitored as well as the spread of pests and the efficiency of the procedures that protect against them. During the surveys, thousands of images are taken of the area, which can be converted to a georeferenced large-sized map within 20 to 40 hours, including post-production and a resolution varying from 0.01 to 0.1 cm/pixel. The paper provides a solution to the industrial post-production of these high-quantity data, in which a deep learning-based automated process using Matlab is presented, including a comparison of the results to the GIS data.