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
Wireless sensor networks (WSNs) have significant potential in many application domains, ranging from precision agriculture and animal welfare to home and office automation. Although sensor network deployments have only begun to appear, the industry still awaits the maturing of this technology to realize its full benefits. The main constraints to large-scale commercial adoption of WSN have been the lack of available network management and control tools, such as for determining the degree of data aggregation prior to transforming it into useful information, localizing the sensors accurately so that timely emergency actions can be taken at an exact location, routing data by reducing sensor energy consumption, and scheduling data packets so that data are sent according to their priority and fairness. Moreover, to the best of our knowledge, no integrated network management solution comprising efficient localization, data scheduling, routing, and data aggregation approaches exists in the literature for a large-scale WSN. Thus, we introduce an integrated network management framework comprising sensor localization, routing, data scheduling, and data aggregation for a large-scale WSN. Experimental results show that the proposed framework outperforms an existing approach that comprises only localization and routing protocols in terms of localization energy consumption, localization error, end-to-end delay, packet loss ratio, and network energy consumption. Moreover, the proposed WSN management framework has potential in building a future "Internet of Things". Copyright (C) 2012 John Wiley & Sons, Ltd.
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