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Open standards and interoperability are key issues in information management for Precision Farming. A collaboration of heterogeneous user groups, from different backgrounds with the need to access common spatial data sets, could benefit with an extensible and open structure with data that can be created and maintained throughout different systems and located in different physical locations (web, machinery, office, etc.).
Open standards and interoperability are key issues in information management for Precision Farming. A collaboration of heterogeneous user groups, from different backgrounds with the need to access common spatial data sets, could benefit with an extensible and open structure with data that can be created and maintained throughout different systems and located in different physical locations (web, machinery, office, etc.).
Agro-industrial companies face the necessity of acquiring more information and control over their crops and the operations they perform in order to produce them. The challenge lies in reducing the hydric and energy resources they use with the objective of increasing their competitiveness and reducing the impact on the environment. Under the brand name of bynse, our SME cubenube (www.cubenube.com) has developed the first big data solution for agriculture in the world.
Agro-industrial companies face the necessity of acquiring more information and control over their crops and the operations they perform in order to produce them. The challenge lies in reducing the hydric and energy resources they use with the objective of increasing their competitiveness and reducing the impact on the environment. Under the brand name of bynse, our SME cubenube (www.cubenube.com) has developed the first big data solution for agriculture in the world.
The project intends to commercialize an integrated precision farming service model in the cloud to increase farming productivity and profitability in a sustainable way. Today, the majority of farmers manage their crop by gut feeling, leading to inappropriate fertilization, plant damage and unnecessary environmental impact.
The project intends to commercialize an integrated precision farming service model in the cloud to increase farming productivity and profitability in a sustainable way. Today, the majority of farmers manage their crop by gut feeling, leading to inappropriate fertilization, plant damage and unnecessary environmental impact.
This phase 2 proposal targets the pilot application and market introduction of AgriCloud, a cloud-based precision farming (PF) management system for more efficient, sustainable production of crops in Europe.
The objectives are:
final technical development,
product demonstration through field trials with six pilot customers,
market launch in five selected EU countries and
market replication leading to a turnover of 28 m € within 5 years after launch.
This phase 2 proposal targets the pilot application and market introduction of AgriCloud, a cloud-based precision farming (PF) management system for more efficient, sustainable production of crops in Europe.
The objectives are:
final technical development,
product demonstration through field trials with six pilot customers,
market launch in five selected EU countries and
market replication leading to a turnover of 28 m € within 5 years after launch.
The data intensive target sector selected for the DataBio project is the Data-Driven Bioeconomy, focusing in production of best possible raw materials from agriculture, forestry and fishery/aquaculture for the bioeconomy industry to produce food, energy and biomaterials taking into account also various responsibility and sustainability issues.
The data intensive target sector selected for the DataBio project is the Data-Driven Bioeconomy, focusing in production of best possible raw materials from agriculture, forestry and fishery/aquaculture for the bioeconomy industry to produce food, energy and biomaterials taking into account also various responsibility and sustainability issues.
SoBigData proposes to create the Social Mining & Big Data Ecosystem: a research infrastructure (RI) providing an integrated ecosystem for ethic-sensitive scientific discoveries and advanced applications of social data mining on the various dimensions of social life, as recorded by “big data”. SoBigData will open up new research avenues in multiple research fields, including mathematics, ICT, and human, social and economic sciences, by enabling easy comparison, re-use and integration of state-of-the-art big social data, methods, and services, into new research.
SoBigData proposes to create the Social Mining & Big Data Ecosystem: a research infrastructure (RI) providing an integrated ecosystem for ethic-sensitive scientific discoveries and advanced applications of social data mining on the various dimensions of social life, as recorded by “big data”. SoBigData will open up new research avenues in multiple research fields, including mathematics, ICT, and human, social and economic sciences, by enabling easy comparison, re-use and integration of state-of-the-art big social data, methods, and services, into new research.
Agri-Ciência was created in 2000 by a research and teaching group from two Portuguese universities. The team members are specialised in several areas which are intertwined and allow the company to provide services in areas such as: agricultural planning, economy and management, IT, databases and GIS. The main business activities of the company are related to information systems applied to agriculture: databases, websites, information management systems, precision agriculture, and decision support systems.
The 'German Network for Bioinformatics Infrastructure – de.NBI' is a national infrastructure supported by the Federal Ministry of Education and Research providing comprehensive, high-quality bioinformatics services to users in life sciences research and biomedicine. The partners organize training events, courses and summer schools on tools, standards and compute services provided by de.NBI to assist researchers to more effectively exploit their data.
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