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With the development and utilization of nuclear energy, the safe operation of nuclear facilities has become a social issue of great concern. China attaches great importance to nuclear emergency plan and the construction of legal, institutional, and mechanism systems. Among them, the emergency preparedness and response of airborne monitoring for nuclear emergency is one of the important components of the national nuclear emergency system. The technology system of airborne monitoring for nuclear emergency is being developed and combines the advantages of manned aircraft and unmanned aerial vehicle (UAV) airborne monitoring. In recent years, UAVs with different loads and types have been developed, with diversified sizes and types of detectors carried by UAVs. The research on UAV airborne monitoring techniques for nuclear emergency has been continuously deepened and improved, and the technical system of airborne monitoring for nuclear emergency has been developed at the same time. The construction of UAV airborne monitoring technology system for nuclear emergency is discussed from the perspectives of monitoring equipment and technology, emergency response plan, emergency monitoring and evaluation, monitoring standards, emergency personnel, emergency support, and training and exercise. The UAV is a rapidly developing aircraft. With the continuous improvement in UAV performance and the continuous innovation and development of nuclear emergency airborne monitoring technology, the UAV airborne monitoring technology system for nuclear emergency will be constantly improved and developed towards networking, intelligence, and standardization.
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In order to test the practicability and operability of the emergency plan for environmental emergencies of district, the ability of radiation accidents quickly respond, emergency monitoring and disposal of the radiation emergency monitoring team, and to inspect cooperative disposal ability according to the responsibilities stipulated in the plan of police department, health department, and publicity departments, and to further standardize the emergency response procedures for radiation accidents, and carry out radiation accident emergency drills. To describe the radiation accident drill organized by the district and jointly held by environmental protection, police department, health department, publicity and other departments, to analyze the scenario design, emergency equipment, emergency monitoring, on-site disposal, emergency termination, and to summarize and analyze the drill. The drill strictly implemented the emergency response procedures for radiation accidents, and comprehensively verified the nuclear and radiation emergency system in Chang'an District. By relying on the existing national technical force, the drill vigorously coordinated and cooperated to improve the rapid response ability of radiation emergency. The drill is an important way to effectively improve the emergency management ability of radiation accidents, to improve the technical ability of effectively response and emergency disposal of radiation environmental safety, and improve the technical level of the emergency monitoring team. It is also one of the technical means for the effective supervision of radioactive sources. It is suggested to continuously carry out the construction of online supervision capability during the transportation of radioactive sources, to improve the professional qualities and skills of road transport operators and reduce the probability of accidents, and continue to strengthen emergency exercises (drills) and technological innovation.
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Objective:To explore the feasibility and effectiveness of the construction of urban unmanned aerial vehicle (UAV) blood distribution system, and to provide a novel way for the distribution of emergency blood.Methods:The study was completed in Hangzhou from April 2019 to January 2021, and the main participants were from the Second Affiliated Hospital of Zhejiang University School of Medicine, Zhejiang Province Blood Center and Hangzhou Fast Ant Network Technology Co., Ltd. Firstly, an unmanned aircraft delivery system was built for urban emergency blood and a special blood storage box for drones were developed. The drone was used to deliver blood products from Zhejiang Province Blood Center to Binjiang Campus, the Second Affiliated Hospital of Zhejiang University School of Medicine, and the following indicators were obtained: (1) flight time of the drone blood delivery; (2) real-time temperature of blood products during transportation; (3) Baidu map software was used to measure the blood delivery time of road traffic, which was compared with the flight time of the drone.Results:The urban drone blood delivery system consists of intelligent logistics drones, cryogenic blood storage tanks, unmanned logistics hub stations, and cloud-based operation control platforms. The drone route distance from Zhejiang Provincial Blood Center to Binjiang Campus, the Second Affiliated Hospital of Zhejiang University School of Medicine was 2.36±0.06 km, and the ground distance was 5.8 km, with 27 flights from April 12, 2019 to January 29, 2021, and the drone flight time was, shorter than the road travel time for a round trip [(6.37±0.35) min vs. (17.00±1.94) min]. At different time points of the day, UAV blood delivery could save 15.98-4.28 min, with an average saving of 10.62±1.87 min. Conclusions:Urban UAV blood delivery systems have the advantages of being fast, unaffected by ground traffic conditions, and can ensure the safety of blood products during transportation, and are worthy of further exploration.
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Objective To evaluate the harmfulness of micro-miniature unmanned aerial vehicles (UAV) to human body, especially to head caused by accidental uncontrolled crash. Methods The dynamic numerical simulation analysis was carried out by using ABAQUS software. The free-falling UAV was simplified in different geometric shapes to impact human head and the damage degree of human head caused by the impact was analyzed. Based on the biological tissue performance parameters, human head and neck was simplified as a mass-spring system and the head was modeled with actual skin texture. Results When the UAV fell from 10 m with weight of 0.5 kg, the abbreviated injury scale (AIS) of the disc-shaped UAV was 1.04, and the AIS of the corn-shaped and sphere-shaped UVA were 1.95 and 2.48. For the UAV with the same geometric shape, as the mass and the falling height increased, both impact acceleration of the head and the AIS increased. When the UAV impacted human head at different angles, the disc-shaped UAV exhibited the smallest impact acceleration, AIS and damage degree. The corn-shaped and sphere-shaped UVAs had small differences in impact acceleration and AIS, but their damage degrees were large. Conclusions When the uncontrolled micro-miniature UAV impacts human head, the mass, height or contact shape of the UAV have a significant influence on the damage degree of human head.
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Unmanned aerial vehicle(UAV) remote sensing and vegetation index have great potential in the field of Chinese herbal medicine planting. In this study, the visible light image of Polygonatum odoratum planting area in Changyi district of Jilin province were acquired by UAV, and the real-time monitoring of P. odoratum planting area was realized. The green leaf index(GLI) was established, and GLI values of P. odoratum were collected used the spatial sampling points. To compare the GLI values in different periods, it was found that the GLI values of P. odoratum have three stages changing rule of rising-gentle-falling related to the germination, vigorous growth and withered of P. odoratum growth. Meanwhile, the GLI values were compared with four biomass data of P. odoratum, including plant height, leaf area, chlorophyll a and chlorophyll b content in leaves, and it was found that the GLI value was related to the growth potential of P. odoratum. The GLI value with a rapid increase in rising stage or at a high level in the gentle stage means the P. odoratum was in a better growth potential. GLI value has a same change trend with plant height, and has certain correlation with plant height and leaf area. However, there is no obvious relationship between chlorophyll a and chlorophyll b contents in leaves and GLI value. The study clarified the change rule of GLI value of P. odoratum, explained the reason for the change of GLI value, and expanded the application range of GLI. The research shows that UAV and vegetation index can be applied to monitoring the Chinese herbal medicines planting, and provides a new idea for exploring more effective information extraction methods of Chinese herbal medicines.
Subject(s)
Chlorophyll A , Plant Leaves , Polygonatum , Remote Sensing TechnologyABSTRACT
The study is aimed to effectively obtain the planting area of traditional Chinese medicine resources. The herbs used as the material for traditional Chinese medicine are mostly planted in natural environment suitable mountainous areas. The UAV low altitude remote sensing data were used as the samples and the GF-2 remote sensing images were applied for the data source to extract the planting area of Salvia miltiorrhiza and Artemisia argyi in Luoning county combined with field investigation. Remote sensing satellite data of standard processing obtain specific remote sensing data coverage. The UAV data were pre-processed to visually interpret the species and distribution of traditional Chinese medicine resources in the sample quadrat. Support vector machine( SVM) was used to classify and estimate the area of traditional Chinese medicine resources in Luoning county,confusion matrix was used to determine the accuracy of spatial distribution of traditional Chinese medicine resources. The result showed that the application of UAV of low altitude remote sensing technology and remote sensing image of satellite in the extraction of S. miltiorrhiza and other varieties planting area was feasible,it also provides a scientific reference for poverty alleviation policies of the traditional Chinese medicine Industry in local areas.Meanwhile,research on remote sensing classification of Chinese medicinal materials based on multi-source and multi-phase high-resolution remote sensing images is actively carried out to explore more effective methods for information extraction of Chinese medicinal materials.
Subject(s)
Altitude , Drugs, Chinese Herbal , Medicine, Chinese Traditional , Natural Resources , Remote Sensing Technology , Support Vector MachineABSTRACT
In order to solve the problem of manual area measurement,the traditional methods of medicinal planting area statistics are difficult to meet the needs of rapid area survey application. This paper uses the UAV remote sensing method with the advantages of unmanned,automatic,high efficiency,high score and short production cycle to monitor the shape of Callicarpa nudiflora. A solution for aerial photography,image data acquisition and data processing of drones were designed for characteristics and planting conditions. After data processing and statistical analysis,detailed information on the location and area of the C. nudiflora in the target area was obtained. Then the accuracy comparison analysis was carried out with the measured results of the C. nudiflora. The results show that the UAV is feasible for the monitoring of C. nudiflora,and has a good application prospect in the monitoring of Chinese herbal medicine planting.
Subject(s)
Callicarpa , Photography , Plants, Medicinal , Remote Sensing TechnologyABSTRACT
An introduction was first given to the advantages and application status of multi-rotor unmanned aerial vehicle (UAV) in the field of medical rescue. Then, the latest worldwide application and research status of multi-rotor UAV in this field were analyzed according to available research. On this basis, the application prospects of multi-rotor UAV in the scenarios of medical rescue field were assumed. Finally, it was pointed out that multi-rotor UAV would show more functions in medical rescue field owing to various technological development and breakthrough, signifying the bright deepening application prospect of multi-rotor UAV.
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ABSTRACT: The Nitrogen content of rice leaves has a significant effect on growth quality and crop yield. We proposed and demonstrated a non-invasive method for the quantitative inversion of rice nitrogen content based on hyperspectral remote sensing data collected by an unmanned aerial vehicle (UAV). Rice canopy albedo images were acquired by a hyperspectral imager onboard an M600-UAV platform. The radiation calibration method was then used to process these data and the reflectance of canopy leaves was acquired. Experimental validation was conducted using the rice field of Shenyang Agricultural University, which was classified into 4 fertilizer levels: zero nitrogen, low nitrogen, normal nitrogen, and high nitrogen. Gaussian process regression (GPR) was then used to train the inversion algorithm to identify specific spectral bands with the highest contribution. This led to a reduction in noise and a higher inversion accuracy. Principal component analysis (PCA) was also used for dimensionality reduction, thereby reducing redundant information and significantly increasing efficiency. A comparison with ground truth measurements demonstrated that the proposed technique was successful in establishing a nitrogen inversion model, the accuracy of which was quantified using a linear fit (R2=0.8525) and the root mean square error (RMSE=0.9507). These results support the use of GPR and provide a theoretical basis for the inversion of rice nitrogen by UAV hyperspectral remote sensing.
RESUMO: O teor de nitrogênio das folhas de arroz tem um efeito significativo sobre a qualidade do crescimento e o rendimento das culturas. Propõe-se e demonstrou-se um método não invasivo para a inversão quantitativa do teor de nitrogênio do arroz com base em dados de detecção remota hiperespectral coletados por um veículo aéreo não tripulado (UAV). As imagens de albedo do dossel de arroz foram adquiridas por uma imagem de imagem hiperespectral a bordo de uma plataforma M600-UAV. O método de calibração da radiação foi então usado para processar esses dados e a reflectância das folhas do dossel foi adquirida. A validação experimental foi realizada utilizando o campo de arroz da Universidade Agrícola de Shenyang, que foi classificado em 4 níveis de fertilizantes: nitrogênio zero, baixo teor de nitrogênio, nitrogênio normal e alto teor de nitrogênio. A regressão do processo gaussiano (GPR) foi então usada para treinar o algoritmo de inversão para identificar bandas espectrais específicas com a maior contribuição. Isso levou a uma redução no ruído e uma maior precisão de inversão. A análise de componentes praincipais (PCA) também foi usada para redução de dimensionalidade, reduzindo assim a informação redundante e aumentando significativamente a eficiência. Uma comparação com as medidas de verdade no solo demonstrou que a técnica proposta foi bem sucedida no estabelecimento de um modelo de inversão de nitrogênio, cuja precisão foi quantificada usando um ajuste linear (R2 = 0,8525) e o erro quadrático médio quadrado (RMSE = 0,9507). Estes resultados suportam o uso do GPR e fornecem uma base teórica para a inversão do nitrogênio do arroz pela detecção remota hiperespectral do UAV.