Abstract
The control of large greenhouse installations, especially those with hydroponics crops, is based on the analysis and use of data recorded by many sensors. At the same time, the size of such installations does not allow for their effective terrestrial surveillance, to detect problems promptly. In recent years, there has been an interest in the development of autonomous agbots equipped with agricultural sensors. Several ground-based AGV (automated guided vehicles) and UAV (unmanned aerial vehicles) systems have been developed for use in open-air plots. A key feature of all these innovative systems is spectroscopy, the development of which has been assisted by the surveillance capabilities and speed of modern-day UAVs (drones). However, there is a lag in the use of spectroscopy inside greenhouses since UAVs do not move freely indoors. In this paper, we propose as a solution a three-device (3DS) system.
Highlights
Today, precision agriculture [1] has taken off with the development of autonomousUAVs (Unmanned Aerial Vehicles) known as drones that help farmers map large areas in a fast and economical way [2,3]
Greenhouse installations lack the benefits of stress maps and prescription maps that can be produced through UAV scouting, as is the case with open fields
Device 2 (D2) will process the collected data and instruct the solenoid valve attached to the zonal irrigation system of a given greenhouse installation or plot
Summary
Precision agriculture [1] has taken off with the development of autonomousUAVs (Unmanned Aerial Vehicles) known as drones that help farmers map large areas in a fast and economical way [2,3]. The data captured by UAVs need to be complemented by other variables such as local climate and soil conditions. A variety of fixed ground stations are cropping up in fields and greenhouses all around the world, collecting soil data and the local climate information. All this information is fed back to an AI engine to produce an actionable prescription map of fertilizer, irrigation or crop protection needs. A sensor placed at a fixed point in a field or a greenhouse does not necessarily record the critical conditions of temporal and spatial variability necessary to make informed decisions. Greenhouse installations lack the benefits of stress maps and prescription maps that can be produced through UAV scouting, as is the case with open fields
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