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
Experiences with deploying Compressive Sensing and Matrix Completion techniques in IoT devices
The Internet of Things (IoT) presents itself as a promising set of technologies for providing innovative smart applications in a number of domains, spreading from agriculture to buildings and industrial control. For providing smart applications in the various domains, large numbers of devices must be deployed within large areas, communicating wirelessly with each other. These IoT devices are mainly resource constrained, with limited computing capabilities and battery life. Furthermore, it is well-known that the most energy consuming operations in wireless devices is the wireless transmission. Thus, there is a strict requirement that to prolong the lifetime of these devices, the transmissions must be controlled. Additionally, communication security is a key issue in many smart applications, because, according to recent studies, there is a lack of secure communication protocols in most existing IoT devices. This paper aims to address these two main issues in the IoT world, providing a framework for lightweight encryption and compression of data using the Compressive Sensing theory, and discusses the experiences of the implementation of the framework on real world devices. Moreover, it is also well-known that the transmissions of wireless sensors are very sensitive to packet loss due to concurrent transmissions of other wireless protocols (i.e. WiFi). This paper also presents the implementation of a framework for applying Matrix Completion techniques in real world IoT devices.
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