TECNICA 16 TECNICA fatti per i vari livelli di automazione oggi possibili: guida, controllo di alcune fasi di lavoro particolarmente delicate, fino ad arrivare alle macchine autonome. Oggi si tratta principalmente di prototipi, ma in qualche caso sono già al lavoro nei campi di tutto il mondo. Partiamo da una delle operazioni più comuni: la guida automatica. Si ottiene, generalmente, con una connessione satellitare, ma in alcuni cadriving. This is usually achieved with a satellite connection, but in some cases a camera system can assist or replace the GPS signal. This occurs, for example, when working between rows, or on particular crops, such as row crops (corn, for example). In these cases, laser or artificial vision systems are more immediate and precise than satellite positioning. A camera mounted on the cutting bar, for example, allows a combine harvester to be easily guided, occupying the entire header and freeing the driver from having to constantly control the direction. An interesting development in this sphere is a recent application proposed by John Deere: a camera system to keep the tractor between the rows of crops when they have not been sown with the aid of satellite. Human planting never forms perfectly straight lines, and using a subsequent self-guided application – for example, weeding – would end up damaging the plants that fall outside the uniform pattern. The camera, on the other hand, diligently follows the rows, even if irregular, keeping the tractor wheels in the inter-row and even controlling the rear equipment. In other cases, the camera provides a surveillance function to certain activities that cannot be controlled by the human eye. For example, a camera placed in the combine harvester's auger tube is able to assess both the amount to recover (grain that escaped the first threshing) and grain breakage, which obviously represent a processing error. No human eye could count the broken kernels in a continuous, rushing flow of grain, but an electronic eye can. Similarly, special cameras are used on tomato harvesters: based on the color of the fruit, they are able to discard the unripe ones, dumping them in the field during harvest. Manual selection is always necessary at the end of the process, but the operators' task is greatly facilitated by the first sorting. In some cases, cameras are used to locate vegetation during specific operations, such as treatments with agrochemicals or herbicides. Due to the cost and danger of the products used, it is extremely important that the spraying is as targeted as possible, and some vehicles use computer vision to automatically turn the nozzles on and off. It should also be said, alternatively, that it is possible to use radar systems for these tasks, which are less affected by the fog created by the vaporization of agrochemicals. At an even higher level of technology, cameras, paired with Un’interessante applicazione delle telecamere all’agricoltura è il controllo della vigoria vegetativa, attraverso camere multispettrali, che contribuiscono a fornire un indice Ndvi (Normalized Difference Vegetation Index) da cui dedurre le zone di coltura con problemi di sviluppo (per scarsità di acqua o nutrienti, terreno soggetto di allagamenti o altro ancora). Questi strumenti possono essere montati su un drone o anche su un trattore o altro mezzo fuoristrada che percorre il campo, mappandone la vigoria. In alcuni casi, la telecamera è abbinata a uno spandiconcime, che adegua in tempo reale il dosaggio alla vigoria rilevata dal sistema di visione artificiale. Più sofisticati ancora i sistemi – ora in fase prototipale – per l’individuazione dei frutti, premessa indispensabile per la costruzione di robot in grado di raccogliere autonomamente le bacche. Scoprire frutti e problemi con la visione artificiale An interesting application of cameras in agriculture is the monitoring of healthy vegetative condition, through multispectral cameras which contribute to provide a Normalized Difference Vegetation Index (NDVI) used to deduce crop areas with development problems (due to water or nutrient scarcity, soil subject to flooding or other). These tools can be mounted on a drone or even on a tractor or other off-road vehicle that drives across the field, mapping out its condition. In some cases, the camera is combined with a fertilizer spreader, which adjusts the dosage in real time to the health detected by the artificial vision system. Even more sophisticated are the systems - now in the prototype stage - that can detect produce, a foundational ability when building robots capable of autonomously picking the fruit. Finding Fruit and Problems with Computer Vision
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