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Faced with the growing imperatives of modern agriculture – ravages of pests, imperative to optimize yields – some farmers are turning to cutting-edge technologies . Today, the joint use of drones and artificial intelligence is one of the most promising alliances to guarantee crop monitoring. This technological synergy not only enables proactive problem detection, but significantly increases agricultural management performance, making the entire process more precise and responsive .
The brown marmorated stink bug: a scourge
Although known for their nauseating odor when crushed, bedbugs represent in reality one of the most formidable agricultural scourges in North America and southern Europe. We are talking here about the brown marmorated stink bug or diabolical stink bug (Halyomorpha halys), originally from Asia. These caused damage estimated at 500 million euros on the Old Continent in 2019 alone. They attack apple trees, pear trees, vines, soybeans or corn. A real calamity on six legs.
Monitoring these pests is essential as they threaten the sustainability of crops. However, the methods currently used are often tedious and inefficient on a large scale. A recent study carried out by Italian researchers and published in the journal Pest Management Science in April looked at< strong> the use of drones equipped with cameras and AI algorithms. They used this system to monitor these bugs in pear orchards.
Agriculture 3.0
For their experiment, the scientists used a commercial drone, the DJI Matrice 300. Equipped with a high-definition camera, it was able to capture very detailed images of the bugs infesting the orchard. By developing an automated flight protocol, they were able to remotely pilot the drone using a mobile application, making it fly over the areas attacked by the insect.
The drone thus captured hundreds of excellent quality shots, then used for training an AI algorithm capable of identifying bedbugs with an accuracy of 97%. Daniele Giannetti, a researcher at the University of Parma and co-author of the study, said: “This innovative surveillance system has demonstrated the potential of integrating drones and AI to detect and quantify the presence of pests “.
200% Deposit Bonus up to €3,000 180% First Deposit Bonus up to $20,000Apart from this experiment, bedbug monitoring is an extremely tiring task. This was mainly carried out through the use of pheromone traps attracting insects, followed by manual counting. A very widespread method, but labor costs are very high and it is much more limited in its effectiveness if we compare it to the drone+AI method.
During the drone's flights, the researchers witnessed some unexpected behavior from the bedbugs. Far from fleeing or falling from the plants, the pests remained perfectly still while the drone flew over them at heights of between 4 and 8 meters. Nearly 85% of the specimens observed exhibited this freezing behavior. A phenomenon that allowed the drone to capture photos of excellent clarity, with the bugs appearing clearly in the frame. Of the 2459 images captured by the drone, 402 contained bedbugs.
The researchers then manually annotated these photos in order to train the algorithm of artificial intelligence, which has proven to be extremely effective in identifying pests in other shots. Although the study focused on bedbugs, scientists believe that the same principles could be applied to monitoring other pests, by exploiting drone images to train AI models specialized in this task.
The integration of drones and artificial intelligence in the agricultural sector therefore opens up exciting prospects for crop management and pest control. Lara Maistrello, professor at the University of Modena and co-author of the study, was particularly convinced: “ This experience is really promising. We welcome these results with great interest, particularly because of the wide range of future applications .” Indeed, other applications are imaginable and just as attractive: soil analyzes, monitoring the expansion of weeds, optimization of irrigation, etc.
- Italian researchers have developed a new kind of protocol to monitor a pear orchard infested with bedbugs.
- They used a drone equipped with & #8217;a camera and fed with AI algorithms to spot bedbugs in trees.
- A method much more effective than traditional methods, which could be applied to other areas of the agricultural sector.
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