Version 1
: Received: 4 August 2024 / Approved: 5 August 2024 / Online: 5 August 2024 (14:39:37 CEST)
How to cite:
Ipate, G.; Ilie, F. Innovative Integrated UAV System for Monitoring Orchards and Vineyards. Preprints2024, 2024080318. https://doi.org/10.20944/preprints202408.0318.v1
Ipate, G.; Ilie, F. Innovative Integrated UAV System for Monitoring Orchards and Vineyards. Preprints 2024, 2024080318. https://doi.org/10.20944/preprints202408.0318.v1
Ipate, G.; Ilie, F. Innovative Integrated UAV System for Monitoring Orchards and Vineyards. Preprints2024, 2024080318. https://doi.org/10.20944/preprints202408.0318.v1
APA Style
Ipate, G., & Ilie, F. (2024). Innovative Integrated UAV System for Monitoring Orchards and Vineyards. Preprints. https://doi.org/10.20944/preprints202408.0318.v1
Chicago/Turabian Style
Ipate, G. and Filip Ilie. 2024 "Innovative Integrated UAV System for Monitoring Orchards and Vineyards" Preprints. https://doi.org/10.20944/preprints202408.0318.v1
Abstract
The main purpose of this study was to create a prototype of an unmanned aerial system equipped with intelligent hardware and software technologies necessary for monitoring the health and growth of crops in orchards. Another important objective was to use low-cost sensors that accurately measure ultraviolet solar radiation. The device, which needs to be attached to the commercial DJI Mini 4 Pro drone, should be small in size, portable, and have very low energy consumption. For this purpose, the widely used Vishay VEML6075 digital optical sensor was selected and implemented in a prototype, alongside a Raspberry Pi Zero 2W minicomputer. To collect data from these sensors, a program written in Python was used, containing specific blocks for data acquisition from each sensor, to facilitate the monitoring of ultraviolet (UV) radiation, or battery current. By analyzing the data obtained from the sensors, several important conclusions are drawn that may provide valuable pathways for the further development of mobile or modular equipment. Furthermore, the results of the plant condition analysis with proposed models in the Geographic Information System (GIS) environment were also presented. The visualization of maps indicating variations in vegetation condition led to the identification of problem areas like hydric stress.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.