FIWARE Open Source Standard Platform in Smart Farming - A Review

[EN] FIWARE is an open source platform for the deployment of Internet of Things (IoT) applications, driven by European Union and managed by FIWARE Foundation. Recently, FIWARE Foundation has launched his new product Agricolus, which focus on Smart Farming and it uses FIWARE infrastructure. Agricolus manages to bring Hardware and Software together in a decision-making process that support farming activities and offers a "plug and play" interface for precision agriculture. This is encompassed by the phenomenon of Smart Farming, which is a development that take advantage of the use of Information Communication Technologies (ICT) in the daily farm management. This review aims to gain insight into the state-of-the-art of FIWARE in Smart Farming and identify the components of Agricolus in comparison with essential FIWARE architecture.This research has been carried out in the framework of the project "Development of an integrated maturity model for agility, resilience and gender perspective in supply chains (MoMARGE). Application to the agricultural sector." Ref. GV/2017/025 funded by the Generalitat Valenciana.Rodríguez-Sánchez, MDLÁ.; Cuenca, L.; Ortiz Bas, Á. (2018). FIWARE Open Source Standard Platform in Smart Farming - A Review. IFIP Advances in Information and Communication Technology. 534:581-589. https://doi.org/10.1007/978-3-319-99127-6_50S581589534Robert, P.C.: Precision agriculture: research needs and status in the USA. In: Stafford, J.V. (ed.) Proceedings of the 2nd European Conference on Precision Agriculture, Part 1, pp. 19–33. Academic Press, SCI/Sheffield (1999)Ge, Y., Thomasson, J.A., Sui, R.: Remote sensing of soil properties in precision agriculture: a review. Front. Earth Sci. 5(3), 229–238 (2011)Sundmaeker, H., Verdouw, C., Wolfert, S., Pérez Freire L.: Internet of food and farm 2020. In: Vermesan, O., Friess, P. (eds.) Digitising the Industry - Internet of Things Connecting Physical, Digital and Virtual Worlds, pp. 129–151. River Publishers, Gistrup/Delft (2016)Lin, J., Liu, C.: Monitoring system based on wireless sensor network and a SocC platform in precision agriculture. In: Proceedings of the International Conference on Communication Technology (ICCT), Hangzhou, pp. 101–104 (2008)Kaewmard, N., Saiyod, S.: Sensor data collection and irrigation control on vegetable crop using smart phone and wireless sensor networks for smart farm. In: Proceedings of the International Conference on Wireless Sensors (ICWiSE), pp. 106–112 (2014)FIWARE. https://www.fiware.org/Future Internet Private Public Partnership (FI-PPP). https://www.fi-ppp.eu/Agricolus. https://www.agricolus.comFIWARE Generic Enablers. http://edu.fiware.org/FIWARE Catalogue. https://catalogue.fiware.org/enablersKamilaris, A., Gao, F., Prenafeta-Boldu, F.X., Ali, M.I.: Agri-IoT: a semantic framework for Internet of Things-enabled smart farming applications. In: IEEE 3rd World Forum on Internet of Things, WF-IoT 2016, pp. 442–447 (2017)López-Riquelme, J.A., Pavón-Pulido, N., Navarro-Hellín, H., Soto-Valles, F., Torres-Sánchez, R.: A software architecture based on FIWARE cloud for precision agriculture. Agric. Water Manag. 183, 123–135 (2017)Martínez, R., Pastor, J.Á., Álvarez, B., Iborra, A.: A testbed to evaluate the FIWARE-based IoT platform in the domain of precision agriculture. Sensors (Switzerland), 16(11) (2016)Pesonen, L.A., et al.: Cropinfra - an internet-based service infrastructure to support crop production in future farms. Biosys. Eng. 120, 92–101 (2014)Barmpounakis, S., et al.: Management and control applications in agriculture domain via a future internet business-to-business platform. Inf. Process. Agric. 2(1), 51–63 (2015)Kaloxylos, A., et al.: Farm management systems and the future internet era. Comput. Electron. Agric. 89, 130–144 (2012)Kaloxylos, A., et al.: A cloud-based farm management system: architecture and implementation. Comput. Electron. Agric. 100, 168–179 (2014)Ryu, M., Yun, J., Miao, T., Ahn, I.Y., Choi, S.C., Kim, J.: Design and implementation of a connected farm for smart farming system. In: 2015 IEEE SENSORS Proceedings, pp. 1–4 (2015)Layton, A.W., Balmos, A.D., Sabpisal, S., Ault, A., Krogmeier, J.V., Buckmaster, D.: ISOBlue: an open source project to bring agricultural machinery data into the cloud, Montreal, 13 July–16 July 2014. American Society of Agricultural and Biological Engineers (2014)SmartAgriFood. http://smartagrifood.com/FIWARE MarketPlace. https://marketplace.fiware.orgFIWARE iHubs. https://www.fiware.org/community/fiware-ihubs/Agricolus in FIWARE MarketPlace. https://marketplace.fiware.org/pages/solutions/2ec3c741ef4dd8f83bab4e83Implementation example of Agricolus. http://www.libelium.com/increasing-tobacco-crops-quality-by-climatic-conditions-control/FIspace. https://www.fispace.eu/whatisfispace.htm

Palaeomagnetic field intensity variations suggest Mesoproterozoic inner-core nucleation

The Earth’s inner core grows by the freezing of liquid iron at its surface. The point in history at which this process initiated marks a step-change in the thermal evolution of the planet. Recent computational and experimental studies1,2,3,4,5 have presented radically differing estimates of the thermal conductivity of the Earth’s core, resulting in estimates of the timing of inner-core nucleation ranging from less than half a billion to nearly two billion years ago. Recent inner-core nucleation (high thermal conductivity) requires high outer-core temperatures in the early Earth that complicate models of thermal evolution. The nucleation of the core leads to a different convective regime6 and potentially different magnetic field structures that produce an observable signal in the palaeomagnetic record and allow the date of inner-core nucleation to be estimated directly. Previous studies searching for this signature have been hampered by the paucity of palaeomagnetic intensity measurements, by the lack of an effective means of assessing their reliability, and by shorter-timescale geomagnetic variations. Here we examine results from an expanded Precambrian database of palaeomagnetic intensity measurements7 selected using a new set of reliability criteria8. Our analysis provides intensity-based support for the dominant dipolarity of the time-averaged Precambrian field, a crucial requirement for palaeomagnetic reconstructions of continents. We also present firm evidence for the existence of very long-term variations in geomagnetic strength. The most prominent and robust transition in the record is an increase in both average field strength and variability that is observed to occur between a billion and 1.5 billion years ago. This observation is most readily explained by the nucleation of the inner core occurring during this interval9; the timing would tend to favour a modest value of core thermal conductivity and supports a simple thermal evolution model for the Earth

Self-Reported Time in Bed and Sleep Quality in Association with Internalizing and Externalizing Symptoms in School-Age Youth

This study investigated the relationship between self-reported time in bed and sleep quality in association with self-reported internalizing and externalizing symptoms in a sample of 285 elementary school students (52% female) recruited from a rural Midwestern elementary school. Path models were used to estimate proposed associations, controlling for grade level and gender. Curvilinear associations were found between time in bed and anxiety, depressive symptoms, and irritability. Marginal curvilinear trends were found between time in bed and emotion dysregulation, reactive aggression, and proactive aggression. Sleep quality was negatively associated with anxiety, depressive symptoms, irritability, reactive aggression, and delinquency engagement. Gender and grade differences were found across models. Findings suggest that examining self-reported time in bed (both linear and quadratic) and sleep quality is important for understanding internalizing and externalizing symptoms associated with sleep in school-age youth. Incorporating self-reported sleep assessments into clinical practice and school-based evaluations may have implications for a child’s adjustment

A school-based physical activity promotion intervention in children: rationale and study protocol for the PREVIENE Project

The lack of physical activity and increasing time spent in sedentary behaviours during childhood place importance on developing low cost, easy-toimplement school-based interventions to increase physical activity among children. The PREVIENE Project will evaluate the effectiveness of five innovative, simple, and feasible interventions (active commuting to/from school, active Physical Education lessons, active school recess, sleep health promotion, and an integrated program incorporating all 4 interventions) to improve physical activity, fitness, anthropometry, sleep health, academic achievement, and health-related quality of life in primary school children. The PREVIENE Project will provide the information about the effectiveness and implementation of different school-based interventions for physical activity promotion in primary school children.The PREVIENE Project was funded by the Spanish Ministry of Economy and Competitiveness (DEP2015-63988-R, MINECO-FEDER). MAG is supported by grants from the Spanish Ministry of Economy and Competitivenes

The use of airborne laser scanning to develop a pixel-based stratification for a verified carbon offset project

Background The voluntary carbon market is a new and growing market that is increasingly important to consider in managing forestland. Monitoring, reporting, and verifying carbon stocks and fluxes at a project level is the single largest direct cost of a forest carbon offset project. There are now many methods for estimating forest stocks with high accuracy that use both Airborne Laser Scanning (ALS) and high-resolution optical remote sensing data. However, many of these methods are not appropriate for use under existing carbon offset standards and most have not been field tested. Results This paper presents a pixel-based forest stratification method that uses both ALS and optical remote sensing data to optimally partition the variability across an ~10,000 ha forest ownership in Mendocino County, CA, USA. This new stratification approach improved the accuracy of the forest inventory, reduced the cost of field-based inventory, and provides a powerful tool for future management planning. This approach also details a method of determining the optimum pixel size to best partition a forest. Conclusions The use of ALS and optical remote sensing data can help reduce the cost of field inventory and can help to locate areas that need the most intensive inventory effort. This pixel-based stratification method may provide a cost-effective approach to reducing inventory costs over larger areas when the remote sensing data acquisition costs can be kept low on a per acre basis

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Analysis of Epithelial and Mesenchymal Markers in Ovarian Cancer Reveals Phenotypic Heterogeneity and Plasticity

Peer reviewe