In this work, objectives were confined into the validation of a Near-Field Communication (NFC) system. Consequently, the use of a decision platform for the management of structures and infrastructures, which is able to gather real-time data from sensors and provide alerts and augmented information about safe paths, paves the way to the adoption of a proactive form of risk management. Emergencies can affect the structural health status of structures and infrastructures and, consequently, the safety in highly populated areas (e.g., urban contexts, occasional assembly points for crowds, theme parks, etc.) is compromised. The obtained results are promising although additional experiments are expected.Ĭatastrophic and accidental natural events (e.g., earthquakes, sudden floods, fires, etc.) and deficiencies in appropriate management activities require proper plans for disaster management and real-time definition of safe paths and escape routes. Therefore, the latter was chosen to analyse the vegetative vigour by applying the VI to onion crop's masks extracted after segmentation and classification of the three images by a geographical object-based image classification (GEOBIA). The results of the analysis of the three datasets showed a high correlation of GNDVI and NDVI vegetation indexes with SAVI. The UAV monitoring has been implemented on three surveys carried out from November 2018 to January 2019. UAV MS imagery were calibrated using a panel with known reflectance and verified with spectroradiometer measurements using the Apogee Ps-300 on bare soil and vegetation. Multitemporal surveys were carried out using the eBee fixed-wing UAV, equipped with a multispectral camera Sequoia Parrot (R-G-RedEdge-NIR). The aim was the monitoring of fields using multispectral imagery acquired by a fixed-wings UAV, and through the use of different vegetation indexes. In the framework of PA, the present paper shows a specific case study applied to the red onion of Tropea (Cipolla Rossa di Tropea) crop. Recently, the International Society for Precision Agriculture (ISPA) defined Precision Agriculture (PA) as 'a management strategy that gathers, processes and analyses temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production'. The latter was chosen to analyze the vegetative vigor by applying the VI to onion crop’s masks extracted after segmentation and classification of the three images by a geographical object-based image classification (GEOBIA). The results of the analysis of the three datasets showed a high correlation of GNDVI and NDVI with SAVI. UAV MS imagery were calibrated using a panel with known reflectance and verified with a spectroradiometer (Apogee Ps-300) on bare soil and vegetation. Multitemporal surveys were carried out using a fixed-wing UAV, equipped with a multispectral camera Sequoia Parrot (R-G-RedEdge-NIR). In the context of PA and with reference to a specific case study on onion crop, the present paper shows the monitoring of fields, using multispectral imagery acquired by UAVs, through the use of different VIs. Precision agriculture (PA) can be considered as management strategy of spatial and temporal variability in fields using information and communications technologies with the aim to optimize profitability, sustainability, and protection of agro-ecological services. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations. The results show that there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil-fuel-energy demand. To demonstrate how this theoretical method works in practice, it is applied as a case study to a current criminal military aggressor nation, who is also a fossil-fuel exporter. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. Hardware is identified that could undercut imports/exports from the target country. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. In this methodology, first the target country that is threatening national security or safety is identified. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. This article reviews the opportunity to use FOSH as a sanction to undercut imports and exports from a target criminal country. Free and open-source hardware (FOSH) development has been shown to increase innovation and reduce economic costs.
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