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Resiliants: WATER

Resiliants: WATER aims to create a predictive dashboard for avocado...

VirtualSense: and augmented sensor for accurate soil moisture measurements

The innovation in precision agriculture involves a system that remotely measures Volumetric Water Content (VWC) using low-cost IoT and AI technologies. It optimizes irrigation in challenging environments.

Set up a pervasive measurement infrastructure for VWC with low-cost devices capable of potentially deploying up to hundreds of sensor nodes
Set up a virtual and augmented sensing techniques for VWC
Set up ML models for inferring VWC over a short-termtime horizon

This innovation addresses the challenges of heavy precipitation, droughts, and heatwaves by optimizing irrigation water use, maximizing crop yields, and increasing the self-sufficiency of the Canary Islands in agricultural products like fruits, vegetables, and textile fibers. Through advanced monitoring and data-driven insights, it enhances the resilience of agriculture in a climate-vulnerable region, ensuring sustainable food production and resource management.

TRL4. Laboratory testing of prototype component or process
The preliminary studies and the scientific research linking RSSI variations, associated with UG2AG wireless links, in function of VWC were accomplished. Then, a preliminary prototype of a sensor node to be buried underground was designed, developed and tested in a laboratory, by taking into account a purely sandy soil. Then, ML models implementing augmented and virtual sensing techniques were designed, developed, trained and tested by firstly collecting an ad-hoc dataset, and then by testing the models in a laboratory by making use of a fully sandy soil. Such activities gave rise to some scientific publications listed below: https://ieeexplore.ieee.org/abstract/document/9128454/https://ieeexplore.ieee.org/abstract/document/9361700https://ieeexplore.ieee.org/abstract/document/9459966https://www.mdpi.com/1424-8220/23/4/2033

See more information about this level and the TRL and SRL levels.

The system’s main components have been individually tested, and an initial integration has been completed.

Credits
CREDITS
Project Manager - Alessandro Pozzebon
Collaborators
COLLABORATORS
Alessandro Pozzebon

How does it work?

Collection and sharing of environmental, agronomic, economic and social data (Canary Islands, Spain)
The proposed innovation relates to this item because the collected data is associated with all of the topics listed above. VWC measurements describe the system deployment site from the environmental and agronomic points of view. Indeed, the content of water in the underground is strictly related to environmental factors like meteorological phenomena. Then, it is much more related to the agronomic perspective since VWC plays a key role in tuning irrigation policies of plantations. Finally, concerning the economic and social aspects, they are a byproduct, since the collected data definitely contributes to enhancing the economic system (specifically the primary sector) of the Canary Islands, which participate in an upgrading of the social system as well.
● Decision-making tools for climate change adaptation in the agricultural sector (Canary Islands, Spain)
The proposed innovation relates to this item because the associated monitoring infrastructure is beneficial for helping decision makers in promptly counteracting the effects of climate change on the agricultural sector. Indeed, irrigation policies can be tuned on the basis of the VWC

The innovation was developed independently as a research activity within the Electronic Measurement research group of the Department of Information Engineering of the University of Padova, Italy.

Owing to the theory standing behind electromagnetic waves propagation through media, the proposed innovation is less effective whenever the sensor nodes forming the WUSN are buried in soils which are not metal free. Indeed, metallic media tend to sensibly attenuate propagation, which translates into a notable effect on RSSIs. However, since VWC estimates are based on RSSI variations, if these are predominantly caused by metal in the underground, rather than dissolved water, such estimates have to be taken into account with a reduced degree of confidence.

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