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
Design of Automatic Cotton Picking Robot with Machine Vision Using Image Processing Algorithms
Agricultural sector is desperately in need of engineering outcomes such as Automation, Information Technology and more recently Robotic Technology. Cotton Cultivation in India occupying a big share in commercial crops is facing a major problem of picking the cotton from the plants by the labor as the labor costs are increasing these days. This paper aims at achieving a prominent solution with the use of Machine vision together with Image Processing and Microcontrollers for identification, recognition, and processing of the cotton image as such and picking the cotton with robotic arms to yield maximum production in a day per hectare. Research and development in perceptual system for robots enabled the agricultural sector to catch hold of the technology in reducing the overall cost. These intelligent robots use variety of visual sensors to detect objects with respect to their identity, position, color, orientation in 3D pattern at the fields. This paper also proposes at the new algorithms in Image processing of the cotton to extract the feature, modeling and matching. These are Artificial Intelligence for Robotic Vision, Image Processing for Segmentation, feature measurement such as invariants, size and shape, texture and scene analysis and controlling the robotic arms in desired angle.
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