4 resultados para Unmanned Aerial Vehicle

em Digital Commons at Florida International University


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Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^

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Mapping of vegetation patterns over large extents using remote sensing methods requires field sample collections for two different purposes: (1) the establishment of plant association classification systems from samples of relative abundance estimates; and (2) training for supervised image classification and accuracy assessment of satellite data derived maps. One challenge for both procedures is the establishment of confidence in results and the analysis across multiple spatial scales. Continuous data sets that enable cross-scale studies are very time consuming and expensive to acquire and such extensive field sampling can be invasive. The use of high resolution aerial photography (hrAP) offers an alternative to extensive, invasive, field sampling and can provide large volume, spatially continuous, reference information that can meet the challenges of confidence building and multi-scale analysis.

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A growing human population, shifting human dietary habits, and climate change are negatively affecting global ecosystems on a massive scale. Expanding agricultural areas to feed a growing population drives extensive habitat loss, and climate change compounds stresses on both food security and ecosystems. Understanding the negative effects of human diet and climate change on agricultural and natural ecosystems provides a context within which potential technological and behavioral solutions can be proposed to help maximize conservation. The purpose of this research was to (1) examine the potential effects of climate change on the suitability of areas for commercial banana plantations in Latin America in the 2050s and how shifts in growing areas could affect protected areas; (2) test the ability of small unmanned aerial vehicles (UAVs) to map productivity of banana plantations as a potential tool for increasing yields and decreasing future plantation expansions; (3) project the effects on biodiversity of increasing rates of animal product consumption in developing megadiverse countries; and (4) estimate the capacity of global pasture biomass production and Fischer-Tropsch hydrocarbon synthesis (IGCC-FT) processing to meet electricity, gasoline and diesel needs. The results indicate that (1) the overall extent of areas suitable for conventional banana cultivation is predicted to decrease by 19% by 2050 because of a hotter and drier climate, but all current banana exporting countries are predicted to maintain some suitable areas with no effects on protected areas; (2) Spatial patterns of NDVI and ENDVI were significantly positively correlated with several metrics of fruit yield and quality, indicating that UAV systems can be used in banana plantations to map spatial patterns of fruit yield; (3) Livestock production is the single largest driver of habitat loss, and both livestock and feedstock production are increasing in developing biodiverse tropical countries. Reducing global animal product consumption should therefore be at the forefront of strategies aimed at reducing biodiversity loss; (4) Removing livestock from global pasture lands and instead utilizing the biomass production could produce enough energy to meet 100% of the electricity, gasoline, and diesel needs of over 40 countries with extensive grassland ecosystems, primarily in tropical developing countries.

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A growing human population, shifting human dietary habits, and climate change are negatively affecting global ecosystems on a massive scale. Expanding agricultural areas to feed a growing population drives extensive habitat loss, and climate change compounds stresses on both food security and ecosystems. Understanding the negative effects of human diet and climate change on agricultural and natural ecosystems provides a context within which potential technological and behavioral solutions can be proposed to help maximize conservation. The purpose of this research was to (1) examine the potential effects of climate change on the suitability of areas for commercial banana plantations in Latin America in the 2050s and how shifts in growing areas could affect protected areas; (2) test the ability of small unmanned aerial vehicles (UAVs) to map productivity of banana plantations as a potential tool for increasing yields and decreasing future plantation expansions; (3) project the effects on biodiversity of increasing rates of animal product consumption in developing megadiverse countries; and (4) estimate the capacity of global pasture biomass production and Fischer-Tropsch hydrocarbon synthesis (IGCC-FT) processing to meet electricity, gasoline and diesel needs. The results indicate that (1) the overall extent of areas suitable for conventional banana cultivation is predicted to decrease by 19% by 2050 because of a hotter and drier climate, but all current banana exporting countries are predicted to maintain some suitable areas with no effects on protected areas; (2) Spatial patterns of NDVI and ENDVI were significantly positively correlated with several metrics of fruit yield and quality, indicating that UAV systems can be used in banana plantations to map spatial patterns of fruit yield; (3) Livestock production is the single largest driver of habitat loss, and both livestock and feedstock production are increasing in developing biodiverse tropical countries. Reducing global animal product consumption should therefore be at the forefront of strategies aimed at reducing biodiversity loss; (4) Removing livestock from global pasture lands and instead utilizing the biomass production could produce enough energy to meet 100% of the electricity, gasoline, and diesel needs of over 40 countries with extensive grassland ecosystems, primarily in tropical developing countries.^