In the context of precision horticulture, decision support tools play a significant role in providing fruit growers with insights into orchard conditions, facilitating informed decisions regarding orchard management practices. This study presents the development of an autonomous yield estimation system designed to provide decision support to small commercial orchards. Autonomous yield estimation is based on the application of UAVs and AI. AI is used to identify and quantify fruitlets and fruits in photographs collected by UAV. In this article, we present our prototype of an autonomous yield estimation system. The adapted “4+1” architecture was applied to design a system with a holistic approach analyzing software, hardware, and ecosystem requirements. Six datasets are presented, which contain the images of fruitlets and fruits of apples, pears, and cherries. Three CNN models were trained: YOLOv8m, YOLOv9m, and YOLOv10m. The experiment showed that the most accurate was YOLOv9m, which achieved mean accuracies of 0.896 mAP@50 and 0.510 mAP@50:95 for all datasets.

Risk analysis is an integral part of modern business management because successful business largely depends on the effective implementation of risk analysis. Agriculture is an important sector in the national economy, therefore Industry 4.0 increasingly provides digital solutions in orchard management, which facilitate and simplify decision-making in daily tasks. Meanwhile, unmanned aerial vehicles are applied as the agriculture sector's main monitoring and data acquisition tool. However, this means that it is necessary to pay attention to risk analysis due to the process of managing the orchard, where not only a person and the mechanized equipment controlled by him, which moves on the ground but also flying automated equipment participates. The purpose of the article is to perform the risk analysis for the survey and monitoring of orchards for yield estimation using unmanned aerial vehicles by considering commercial apple orchards in Latvia. The main thing is that most risks are predictable, but planning is necessary to reduce the probability of their occurrence.

Laser marking technology today is a key part of the production of many products and devices used in our daily lives. At the same time, for specific types of products, the process must be optimized depending on the material used, laser system and marking method. Copper is such a metal that has a number of applications in the military industry, electrical engineering, electronics, household, etc. The scientific report investigates the influence of the technological parameters speed, raster step and number of repetitions on the contrast and roughness of marking for copper samples. A fiber laser technology system was used to perform the experiments, and the roughness measurements were performed with an OLS 5000 laser microscope. A wide range of marking speeds from 10 mm/s to 1500 mm/s was selected, where the contrast and roughness behavior of the marking is tracked for different raster steps in both single marking and double marking. It was found that as the speed increased, the contrast and roughness decreased. Also, with double marking, the contrast and roughness values are higher than with single marking. The velocity intervals in which the contrast has positive values and those in which it has negative values are established. The regularity was obtained that increasing the step of the raster leads to a decrease in contrast and an increase in roughness.

Functional textile are one of the most critical fields in the textile industry and textile materials science. In recent years, advanced technologies in textile processing have become relevant in order to improve its usability. In the production of various types of functional textile, one of the methods is the modification of textile surfaces. To improve the properties of the textile surface, magnetron vacuum sputtering and laser post-processing technologies can be used, which in general gives the material new or improved properties and functionalities. In this study, mixed fiber fabrics containing polyester, protal and cotton fibers are used to determine how laser post-treatment of the metalized fabrics impact the adhesive properties between fabric and deposited metal. The following materials were used for magnetron vacuum sputtering for functional textile coatings: Cu, Al, Ti, Ag. Individually or by combining these metals, it is possible to assign the textile such properties as: electromagnetic, UV and IR radiation shielding; antistatic, antibacterial, hydrophilic and hydrophobic properties, as well as increasing wear resistance. In this study a 100 W continuous wave CO2 laser with a wavelength of 10.6 µm is used for post-treatment of magnetron vacuum sputtered modified textile surfaces. The study's conclusions point towards a tailored approach in determining linear energy densities that bolster adhesion for each metal-textile combination, which is essential for the development of durable and functional advanced textile. The patterns noted in the adhesion strengths, influenced by different energy densities and metal types, highlight the intricate relationship between the thermal impact of laser treatment and the inherent characteristics of the metals deposited. Some metals demonstrated improved adhesion at lower energy densities. However, a general trend emerged showing a reduction in the strength of adhesion as the energy density increased, especially when surpassing certain energy levels.

This study examines the texturing of anodized aluminium using a Rofin PowerLine F 20 Varia nanosecond Yb doped fiber laser. It explores how varying laser parameters like scanning speed, hatching step, laser power, and frequency impact the surface's wetting properties, particularly the contact angle with a water droplet. The research aims to understand the influence of these parameters on the aluminium’s surface, offering insights into the laser micromachining process and its industrial and material science applications. This study examines the texturing of anodized aluminium using a Rofin PowerLine F 20 Varia nanosecond Yb doped fiber laser. It explores how varying laser parameters like scanning speed, hatching step, laser power, and frequency impact the surface's wetting properties, particularly the contact angle with a water droplet. The research aims to understand the influence of these parameters on the aluminium’s surface, offering insights into the laser micromachining process and its industrial and material science applications. This study investigates the texturing of anodized aluminium using a Rofin PowerLine F20 Varia nanosecond fiber laser. It investigates how different laser parameters such as scan speed, hatching step, laser power and frequency affect the surface wetting properties, especially the contact angle of a water droplet. The research aims to understand the influence of these parameters on the aluminium surface, offering insights into the laser micromachining process and its applications in industry and materials science.

This study investigates the use of a CuBr vapor nanosecond laser with a 510 nm/578.2 nm wavelength for the surface treatment of 1050 aluminum and 2219 aluminum alloys. Laser-induced periodic surface structuring was used to optimize processing parameters to achieve hydrophobic and hydrophilic properties on the surface. The wetting properties were measured and the roughness results (R_a, R_z, R_q) evaluated. Prior to and after laser treatment, surface wetting and roughness changes were investigated. The wetting study showed that the maximum contact angle between a droplet of deionized water and the treated surface can be reached between more than 140 degrees and less than 10 degrees, which, respectively, is a superhydrophobic and superhydrophilic surface. Compared with the untreated surface, wetting increased by more than 2 times and decreased by more than 8 times. Overall, experiments show the dependence of wetting properties on laser input parameters such as scan speed and scan line distance with different delivered energy amounts. This study demonstrates the possibility of laser parameter optimizations which do not require auxiliary gases and additional processing of the resulting surfaces to obtain different wetting properties on the surface. The findings described in this article suggest that the CuBr laser surface treatment method is a promising method for industrial applications where surfaces with special wetting and roughness properties are required, for example, the laser marking of the serial number of parts used in wet environments such as aerospace, shipbuilding, and defense industries.