Search Results (7)

Hexagonal boron nitride (h-BN) has emerged as a promising dielectric material for protecting metallic substrates such as copper and steel under ambient conditions. The layered structure of h-BN offers significant potential in preventing the oxidation and corrosion of these substrates. Due to their impermeability, boron nitride nanosheets (BNNSs) do not form a galvanic cell with the underlying metals, enhancing their effectiveness as protective coatings. BNNSs are both thermally and chemically stable, making them suitable for coatings that protect against environmental degradation. Additionally, BNNSs have demonstrated excellent fire resistance, hydrophobicity, and oxidation resistance when applied to wood, functioning as a binder-free, retardant coating that remains effective up to 900 °C in air. This review focuses on the anti-corrosion properties of BNNSs, particularly on copper and steel substrates, and discusses various methods for their application. This article also discusses future perspectives in this field, including the innovative concept of wooden satellites designed for short- and long-term missions. Full article

Agrivoltaics is defined as “the dual use of land for solar energy production and agriculture”. On this topic, a number of issues are still to be properly addressed, e.g., how the shading effect of the solar panels affects crop growth. In this work, the development of a large-scale digital twin model to predict crop yield under varying solar panel coverage is discussed. A framework is proposed to exploit Internet of Things (IoT) concepts, with a sensor network to collect data on the field merged with sensor fusion to possibly handle information gathered by satellite images. The aim of the entire work is related to the synergic optimization of energy production and crop yield, and data analytics based on artificial intelligence tools are to be extensively developed. Herein, the results are reported of an experimental activity, currently under way at the Fantoli laboratory of Politecnico di Milano. Wooden panels, placed above the crops with a varying pattern, are used to study the shading effect with a specific target on the conditions typical of Northern Italy. The laboratory facility is equipped with a comprehensive sensor network to acquire the data necessary to build the targeted large-scale digital twin of the agrivoltaic system. Full article

Enhancing the livelihood environment for fishermen’s communities with the rapid technological growth is essential in the marine sector. Among the various issues in the fishing industry, fishing zone identification and fish catch detection play a significant role in the fishing community. In this work, the automated prediction of potential fishing zones and classification of fish species in an aquatic environment through machine learning algorithms is developed and implemented. A prototype of the boat structure is designed and developed with lightweight wooden material encompassing all necessary sensors and cameras. The functions of the unmanned boat (FishID-AUV) are based on the user’s control through a user-friendly mobile/web application (APP). The different features impacting the identification of hotspots are considered, and feature selection is performed using various classifier-based learning algorithms, namely, Naive Bayes, Nearest neighbors, Random Forest and Support Vector Machine (SVM). The performance of classifications are compared. From the real-time results, it is clear that the Naive Bayes classification model is found to provide better accuracy, which is employed in the application platform for predicting the potential fishing zone. After identifying the first catch, the species are classified using an AlexNet-based deep Convolutional Neural Network. Also, the user can fetch real-time information such as the status of fishing through live video streaming to determine the quality and quantity of fish along with information like pH, temperature and humidity. The proposed work is implemented in a real-time boat structure prototype and is validated with data from sensors and satellites. Full article

Large-area, artificial floating marine litter (FML) targets were deployed during a controlled field experiment and data acquisition campaign: the Plastic Litter Project 2021. A set of 22 Sentinel-2 images, along with UAS data and ancillary measurements were acquired. Spectral analysis of the FML and natural debris (wooden planks) targets was performed, along with spectral comparison and separability analysis between FML and other floating materials such as marine mucilage and pollen. The effects of biofouling and submersion on the spectral signal of FML were also investigated under realistic field conditions. Detection of FML is performed through a partial unmixing methodology. Floating substances such as pollen exhibit similar spectral characteristics to FML, and are difficult to differentiate. Biofouling is shown to affect the magnitude and shape of the FML signal mainly in the RGB bands, with less significant effect on the infrared part of the spectrum. Submersion affects the FML signal throughout the range of the Sentinel-2 satellite, with the most significant effect in the NIR part of the spectrum. Sentinel-2 detection of FML can be successfully performed through a partial unmixing methodology for FML concentrations with abundance fractions of 20%, under reasonable conditions. Full article

Rapid urbanization has led to several severe environmental problems, including so-called heat island effects, which can be mitigated by creating more urban green spaces. However, the temperature of various surfaces differs and precise measurement and analyses are required to determine the “coolest” of these. Therefore, we evaluated the accuracy of surface temperature data based on thermal infrared (TIR) cameras mounted on unmanned aerial vehicles (UAVs), which have recently been utilized for the spatial analysis of surface temperatures. Accordingly, we investigated land surface temperatures (LSTs) in green spaces, specifically those of different land cover types in an urban park in Korea. We compared and analyzed LST data generated by a thermal infrared (TIR) camera mounted on an unmanned aerial vehicle (UAV) and LST data from the Landsat 8 satellite for seven specific periods. For comparison and evaluation, we measured in situ LSTs using contact thermometers. The UAV TIR LST showed higher accuracy (R² 0.912, root mean square error (RMSE) 3.502 °C) than Landsat TIR LST accuracy (R² value lower than 0.3 and RMSE of 7.246 °C) in all periods. The Landsat TIR LST did not show distinct LST characteristics by period and land cover type; however, grassland, the largest land cover type in the study area, showed the highest accuracy. With regard to the accuracy of the UAV TIR LST by season, the accuracy was higher in summer and spring ($R^2$ 0.868–0.915, RMSE 2.523–3.499 °C) than in autumn and winter ($R^2$ 0.766–0.79, RMSE 3.834–5.398 °C). Some land cover types (concrete bike path, wooden deck) were overestimated, showing relatively high total RMSEs of 4.439 °C and 3.897 °C, respectively, whereas grassland, which has lower LST, was underestimated—showing a total RMSE of 3.316 °C. Our results showed that the UAV TIR LST could be measured with sufficient reliability for each season and land cover type in an urban park with complex land cover types. Accordingly, our results could contribute to decision-making for urban spaces and environmental planning in consideration of the thermal environment. Full article

The purpose of this study was to better understand the relationships between diurnal variations of air temperature measured hourly at the soil surface, compared with the thermal infra-red (TIR) emission properties of soil surfaces located in the Lower Colorado Desert of California, eastern Riverside County. Fifty air temperature loggers were deployed in January of 2017 on wooden stakes that were driven into the sandy or rocky desert soils at both Ford Dry Lake and the southern McCoy Mountains wash. The land surface temperature (LST) derived from Landsat satellite images was compared to measured air temperatures at 1 m and at the soil surface on 14 separate dates, until mid-September, 2017. Results showed that it is feasible to derive estimated temperatures at the soil surface from hourly air temperatures, recorded at 1 m above the surface (ambient). The study further correlated Landsat LST closely with site measurements of air and surface temperatures in these solar energy development zones of southern California, allowing inter-conversion with ground-based measurements for use in ecosystem change and animal population biology studies. Full article

Satellite imagery has had limited application in the analysis of pre-colonial settlement archaeology in the Caribbean; visible evidence of wooden structures perishes quickly in tropical climates. Only slight topographic modifications remain, typically associated with middens. Nonetheless, surface scatters, as well as the soil characteristics they produce, can serve as quantifiable indicators of an archaeological site, detectable by analyzing remote sensing imagery. A variety of pre-processed, very diverse data sets went through a process of image registration, with the intention to combine multispectral bands to feed two different semi-automatic direct detection algorithms: a posterior probability, and a frequentist approach. Two 5 × 5 km² areas in the northwestern Dominican Republic with diverse environments, having sufficient imagery coverage, and a representative number of known indigenous site locations, served each for one approach. Buffers around the locations of known sites, as well as areas with no likely archaeological evidence were used as samples. The resulting maps offer quantifiable statistical outcomes of locations with similar pixel value combinations as the identified sites, indicating higher probability of archaeological evidence. These still very experimental and rather unvalidated trials, as they have not been subsequently groundtruthed, show variable potential of this method in diverse environments. Full article