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
Nowadays, more and more researchers focus on the Internet of Things (IoT), which blurs the line between virtual and real worlds. However, few of them concern how to realize this kind of applications. In order to do some further study on the software implementation, in this paper, we propose a model of Internet of things used in agriculture, named AGIOT. A new four-layer architecture of the IoT application is established and some key issues in system implementation are discussed. Further more, a new middle layer framework is presented based on service oriented architecture (SOA), which makes users access to real-time data easily through a high-level abstract interface based on web services. In order to increase the yield and improve the quality of plant, an intelligent algorithm based on reinforcement learning is introduced. The model we proposed is feasible.
Inappropriate format for Document type, expected simple value but got array, please use list format