big data

The project aims to develop novel IoT technologies and study their applications in water management. The automatic data collection storage and processing using HPC and other high performance processing tools to run advanced models on data interpretation and dynamics forecasting in real time.
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The objective of the FIGARO project is to significantly reduce the use of fresh water on farm level through developing a cost-effective, precision irrigation management platform. The platform will be structured for data acquisition from monitoring devices and forecasting tools, data interpretation, system control, and evaluation mechanisms enabling full decision support for end users at farm scale. These tools will be integrated with multiple state-of-the-art irrigation technologies and strategies as well as newly adapted devices leading to further increased water productivity.
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This project is funded by the innovation program of the Federal Ministry of Food and Agriculture (BMEL), funding agency is the Federal Office for Agriculture and Food (BLE). Orchestration of Process Chains for data-driven Resource Optimization in Agricultural Business and Engineering Environmentally sustainable and economically efficient operation of agricultural processes depends heavily on farm management and controlling systems. However, practical usage of these systems suffers from diverse, non-compatible implementations across collaboration machinery.
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The major objective is to develop indigenous prototype for drone based crop and soil health monitoring system using hyperspectral remote sensing (HRS) sensors. This technology could also be integrated with satellite-based technologies for large scale applications Drone technology based unmanned aerial vehicle (UAV) has ability for smooth scouting over farm fields, gathering precise information and transmitting the data on real time basis.
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The present production and delivery of real-time crop protection information is not optimal and there are bottlenecks to work on. This project will renew the way this valuable information is produced, shared and delivered. With an easy-to-use app, we shall activate farmers and forest owners to monitor crop pests. Together with helping to carry out monitoring and making and sharing pest observations the app service will be capable of delivering up-to-date expert information on crop pests and pathogens. The project participants share and build commitment to produce this expert information.
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FATIMA addresses effective and efficient monitoring and management of agricultural resources to achieve optimum crop yield and quality in a sustainable environment. It covers both ends of the scale relevant for food production, viz., precision farming and the perspective of a sustainable agriculture in the context of integrated agri-environment management.
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The project will design, develop and implement a Future Internet based Sustainable Irrigation Service (FISIS), which will allow end users to increase yield and, at the same time, significantly reduce both economic and environmental cost. FISIS will stimulate social networking and collective awareness among end users, targeting the dissemination of best practices, exchange of opinions, discussions and advice from experts.
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Research, domains and case projects While some questions in the core disciplines will be addressed using traditional research approaches, many of the main activities in the partnership will be orchestrated in a number of case projects. A project will have a clear business potential and address challenges that can be met using the knowledge, methods and services of the core. Most of the initially defined projects fall within the three domains, but cross-cutting projects and new opportunities are expected to appear during the partnership.
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The truly innovative idea of this partnership is to integrate data from distributed information sources to provide new technologies, solutions and cultivation techniques for modern high yielding and low emis-sion precision farming. The com-mercial output targets optimization of key operations in the cropping cycle by balancing profitability for the farmer with risk of unintended emissions from fields and subsur-face.
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Within the pilot project Smart Dairy Farming, companies, research institutes and farmers together to develop innovative resources in the field of animal health, fertility and nutrition. This means farmers can extend the life of their cows. The concrete result consists of sensors, indicators, decision models and advisory products that help in making the right choices when caring for cows. Proper care contributes to better health and longer life expectancy of the animals. Thus, this project contributes to the sustainability of the chain.
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On the internet is a wealth of data freely available: Websites and Social Media provide information on using experiences of consumers and their questions about products. Open Data from public and private sources provide insight into the expected supply of products. Horticulture companies make little use of this wealth, precisely at a time when market information is of such importance. Two factors hindering the efficient use of data. First, the necessary investments and knowledge go beyond the capacities of individual companies.
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SAGIRA project has developed a system to analyze information from farming sensors, georeferenced, with specicialised stock and with an interface display which show the result data overprinted on the real images (augmented reality with mobile devices). This technology allows users to make relations between elements, not only pay attention on characteristics of them, as historically. Furthermore, users can check data using these relations and attributes. It is useful to optimization of water resources in crops and pesticides and fertilizers.
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Efficient agriculture water use is of crucial importance for water resources management. Consequently, accurately determining evapotranspiration (ET) is the first step for improving irrigation efficiency and productivity and for quantifying the ecosystem water balance. Several approaches for determining ET have been proposed in literature, but the relation between high and low spatial resolution methods still remains unresolved in irrigation studies and water management planning.
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Domopig is a research project whose aim it aims to create a platform to promote computer data of pig farms in order to optimize management. One of the idea, is to make interoperable all data recorded in a farm pigs to drive the livestock within a single interface and analyze all data collected to improve the livestock production. Funding by "Région Bretagne" https://www.youtube.com/watch?v=sJA9i64M3mY
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The project goal is to create an infrastructure that will permit to evaluate data in precision livestock farming along the value chain with the stages breeding/piglet production, fattening, and slaughterhouse across farms, farming branches, applications and standards. This includes data from external sources, e.g. on veterinary medical products and feed stuff. The results of the project are generic semantic models, which describe data independent of their syntactic structure and thus allow to easily convert data between different formats of representation.
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