Researchers have developed a deep learning and laser system to detect and repel wild birds, effectively protecting crops and poultry. The system, tested on a duck farm in Taiwan, significantly reduced bird presence with a repulsion rate of up to 97.1% per hour.
Researchers introduced HDMNet, a deep learning-based visual system for robotic pear picking, enhancing YOLOv8 with three key features for better accuracy and efficiency in complex environments. HDMNet demonstrated superior performance in real-time detection, achieving a high mean average precision and operating seamlessly in real-world applications, promising significant advancements in agricultural automation.
Researchers developed CES-YOLOv8, an advanced deep learning algorithm, to improve the accuracy and efficiency of detecting strawberry ripeness for automated harvesting robots. CES-YOLOv8 demonstrated superior performance in real-time image processing, offering significant advancements in smart agriculture and potential applications for various fruit crops.
An international group of researchers from Tampere University and the University of Pittsburgh created a tiny robot to mimic the airborne dance of falling maple seeds.
Scientists at Umeå University have successfully developed an artificial intelligence-driven, self-driving forest machine that can run a 16-ton machine without human assistance.
In a recent study published in the scientific journal Nature Sustainability, a team led by Moussa El Jarroudi from the University of Liège demonstrates how to overcome challenges and how artificial intelligence can be practically integrated into agricultural systems to meet the expanding needs of sustainable food production.
A new AI system that counts flowers on fruit trees is helping farmers to predict harvest sizes months in advance, making crop yields more efficient, sustainable, and profitable.
Researchers in Italy have announced the first effective use of commercial drones and artificial intelligence (AI) to monitor the invasive agricultural pest, Halyomorpha halys, also known as the brown marmorated stink bug.
A recent Agronomy article highlights the transformative potential of AI, sensors, and robotics in agriculture, focusing on their roles in enhancing efficiency, productivity, and sustainability. While these technologies promise significant advancements, challenges like high costs and complexity remain, necessitating further research and collaboration among stakeholders.
Researchers from the University of Southampton employ AI and drones to find a mate for the critically endangered Encephalartos woodii, an ancient plant species. Their interdisciplinary approach blends science, technology, and art to save this species from extinction, inspiring hope and innovation in conservation efforts.
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