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
An Intelligent Controlling System for Greenhouse Environment Based on the Architecture of the Internet of Things
Greenhouse farming possesses substantial potential in high-efficiency use of water, land and energy in food production. It is a critical issue to develop the methodology for better environment control of greenhouses. This paper proposes an intelligent controlling system for greenhouses based on the architecture of the Internet of Things. The wireless sensor nodes and relay nodes are designed associating the physical world with the information world. Using 3G or TCP/IP network as the channel of the network of the Internet of Things, users can completely control the systems, treat and analyze data via browsers in any place and at any time without need for installing any special device or software. The system carries out the paradigm of the Dynamic Data Driven Application System enabling the simulation to receive the continuous data injected from the perception layer of the system and to dynamically make response. The faster-than-real-time simulation is implemented based on the established self-adaptation model. The factors about the environments of crop growing are predicted and evaluated. At the same time, the results produced by the simulation are fed back to the system software to control the actions of executive devices in the real-time mode forming a closed controlling loop. The management function of the system software allows to flexibly set the executive devises of the greenhouses and to establish the completely new controlling rules with high degree of freedom. Consequently, the software system combined with the expert system can adapt to various greenhouses in different types and sizes.
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