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
Framework and Case Studies of Intelligence Monitoring Platform in Facility Agriculture Ecosystem
Facility agriculture area in China is expanding, and is leading the world. However its ecosystem control technology and system is still immature, with low level of intelligence. This puts significant constrain on the efficient, high-quality, safe and sustainable production of facility agriculture. Promoting application of modern information technology in agriculture will solve a series of technical questions in information collection in wide area, efficient and reliable information transmission, intelligent system integration for different needs and environment. This will be a catalyst for the transition from traditional farming to modern farming. This also provides opportunity for creating new technology and service development in IOT (internet of things) farming application. This paper presents an intelligent monitoring platform framework and system structure for facility agriculture ecosystem based on JOT. The solution is divided into four function layers based on the difference in information exchange process and task logical handling, i.e. sensor layer, transmission layer, monitoring layer, application layer. Among them, sensor layer is responsible for numerical sensor of physical values in farming. The sensor module formats and processes collected data based on public standard, and transforms to information and stores. The transmission layer summarizes collected data from sensor layer, using internet technology e. g. wireless sensor network. It provides data for upper layer to invoke, analyze and process. The monitoring layer uses the summarized data as input parameters, and intellectually control task in farming, by regulating automatic control algorithm. It results in better ecosystem that better suits crops' growth, reduces human interference, and eventually achieves more accurate farming process. The application layer summarizes and analyzes huge volume of information across locations and industries, through advanced open-ness and intelligence. It helps build up the industry's information service on environment, and better supports decision-making and action. The same rules are used in communication between different layers. Adjacent layers in the same system use standard interface to transmit data. This paper applies the above-mentioned framework in intelligent monitoring platform of facility agriculture ecosystem in Shanghai, and analyzes and verifies the whole implementation process and selection of decision-making model. This framework is proven to be reliable and adaptable.
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