The e-ROSA project seeks to build a shared vision of a future sustainable e-infrastructure for research and education in agriculture in order to promote Open Science in this field and as such contribute to addressing related societal challenges. In order to achieve this goal, e-ROSA’s first objective is to bring together the relevant scientific communities and stakeholders and engage them in the process of coelaboration of an ambitious, practical roadmap that provides the basis for the design and implementation of such an e-infrastructure in the years to come.
This website highlights the results of a bibliometric analysis conducted at a global scale in order to identify key scientists and associated research performing organisations (e.g. public research institutes, universities, Research & Development departments of private companies) that work in the field of agricultural data sources and services. If you have any comment or feedback on the bibliometric study, please use the online form.
You can access and play with the graphs:
- Evolution of the number of publications between 2005 and 2015
- Map of most publishing countries between 2005 and 2015
- Network of country collaborations
- Network of institutional collaborations (+10 publications)
- Network of keywords relating to data - Link
A wireless data fusion system was designed to automatically collect and process operational data from agricultural machinery in order to provide real-time support for precision farming tasks. The system provides transparent data management and decision_support functions to crop producers by wirelessly integrating a machinery-based sensing unit and an office-based data processing unit. The machinery-based unit collects the machine position and attitude data, the office-based unit performs data fusion to accurately estimate the machine position, and the wireless data-link transmits the data between the machinery- and the office-based units. Field tests indicate that this system can collect field data from the operating machinery and wirelessly send the raw data to a data-processing centre to acquire accurate machinery positioning data at a sampling rate of 50 Hz. The wireless data-link can transmit data between the machinery- and the office-based units at 2 Mb/s within a 3.2 km radius. Results verify that this newly developed wireless data fusion system is capable of handling field data in real-time to support data-intensive precision farming operations. (c) 2005 Silsoe Research Institute. All rights reserved Published by Elsevier Ltd.
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