Precision agriculture (PA), satellite farming or site-specific crop management (SSCM) is a farming management concept based on observing, measuring and responding to inter and intra-field variability in crops. Today, even though significant effort has been put on making innovative precision agriculture technologies, the actual adoption of the innovation has been notoriously slow. The biggest problem most of the newest technologies have, is the time and effort overhead added to the farmer.

NebulOuS' agriculture use case

When there is a need to decide on how much fertilizer must be sprayed into which part of a field then a drone can be used to generate a site-specific map. A prerequisite is when the drone is going to be used, first the weather should be appropriate and second that 7 to 10 days can be speared for waiting on the video feeds and images translation to actionable data. Then, the farmer can exploit the data and perform a “guided” fertilization, which of course is valuable both due to costs reduction but also due to environmental benefits (reducing the fertilizers used). Currently, AuG exploits edge devices with both CPU and GPU processing power in the field, in order to provide real-time image processing for tractors that are able to execute the whole operation of fertilization with one tractor pass, in real time. AuG is able to gather 4K frames from 3 to 18 different cameras with a rate of 4 times per second. That massive amount of information to be processed on the edge, generate additional challenges (e.g., raw frames from fields might be critical to detect things like fungi).

The goal of NebulOuS is enhancing all the data processing jobs to their fullest potential. It is clear that integrating an innovative solution like NebulOuS in AuG’s solution, gives a plethora of capabilities on the diversification of data handling into various different sources, taking advantage of the pros and cons of each type of resource and finally making a cost-effective solution that also augments the capabilities of AuG’s hardware & machine learning infrastructure. NebulOuS technology will enable AuG’s device to allocate some of the data streams propagation and processing to a combination of heterogeneous micro local clouds, private clouds, public clouds as well as edge resources. Moreover, NebulOuS platform is a perfect way of micromanaging processing jobs that can be time-critical like pattern recognition for spotting low vegetation areas that do not need any fertilizer or post-operational analysis applications like leaf pattern recognition for spotting certain diseases. Last, the aspect of security is of the highest importance, as farm data are confidential and owned by the farm owner, so the propagation of data, processing and persistence should be properly secured.

Operation & Deployment of Use Case: Augmenta will mount a state-of-the-art hardware device on top of tractors and will analyse the farm in real time as the tractor is moving forward in the field. AuG’s device controls agricultural machinery, like sprayers or spreaders in real time, in order to provide the necessary chemicals to every part of the field with the goal of reducing average inputs, increasing the yield quantity and quality while protecting the environment. The pilot will be conducted in 2 different farms of 5 to 10 hectares in Perivlepto, Thessaly, Greece, which is where Augmenta conducts their field R&D.

Main Partners Supporting the Use Case:

AuG (France, SME): state-of-the-art hardware platform provider.
UBI (Greece, SME): Private edge computing and 5G testbed provider.

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Directorate-General for Communications Networks, Content and Technology. Neither the European Union nor the granting authority can be held responsible for them.

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