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Resiliants: WATER

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

Personalised Sustainability. Remote sensing applied to our agricultural/environmental environment.

This innovation focuses on sustainable agriculture in the Canary Islands by integrating satellite and drone data to monitor and improve soil health, water usage, and biodiversity.

It allows a large number of parameters to be covered and monitored at the same time without the need for physical samples.
It allows a very large area to be covered with the same effort and with moderate adverse conditions it would allow permanent monitoring of quality 365 days a year.
With a single flight it is possible to monitor different plots, but also different plots with different orography, distance, proximity to the sea, regardless of thecomplexity of access or crops.

Our innovation addresses critical climate-related hazards, including droughts, wildfires, and multi-hazard scenarios, by focusing on comprehensive environmental management. It aims to solve the following key problems:

Drinking Water Management: Ensures sustainable water use and conservation strategies to mitigate drought impacts.

Restore Topsoil: Implements techniques for soil restoration, improving agricultural productivity and reducing erosion.

Biodiversity: Protects and enhances biodiversity, crucial for ecosystem resilience against climate hazards.
GHG and CO2 Emissions: Reduces greenhouse gas emissions through sustainable practices in agriculture and land management.

Own Waste: Manages waste generated by agricultural practices, minimizing environmental contamination.

Aquatic Ecosystems: Safeguards water bodies from pollution and supports aquatic ecosystem health.

Dissemination and Training: Provides education and training to communities and stakeholders, promoting sustainable practices and resilience against climate impacts.

This holistic approach not only addresses immediate environmental concerns but also promotes long-term sustainability and community engagement.

TRL4. Laboratory testing of prototype component or process
Sensor integration issues will be resolved. Deployments in complex areas will be solved or improved. Agro information will be provided in a fast and/or effective way, depending on the historical yields of the plot and the evolution of the plot during the study period. Characteristics: Environment testing: The data capture technology has been tested in conditions that resemble the real situations in which it will be used and has been validated at a basic level. Key components and features: The key components and features of the technology are being developed and subsequently tested individually, they are not yet integrated into a functional system. Demonstrated performance: The technology is shown to work as intended, but will require optimizations and improvements to achieve the final objectives. The application of artificial intelligence AI algorithms for certain processes will allow us to use agile and methodical processes in the transformation of data into quality information applicable to the proposed objectives; knowing that an algorithm is no more or less than an unambiguous recipe that, based on the ingredients provided, will always be executed in the same way to achieve the same result in the end. Risk assessment: The main technical risks and obstacles in development have been identified and addressed, although some minor risks may still exist. Interdisciplinary collaboration: Development teams need to involve experts from other disciplines to work together to resolve issues and bring the technology to a more mature level. It is important to keep in mind that the path from TRL 4 to commercial implementation or operational adoption is a complex process and may take additional time and resources. The technology must progress through higher levels of TRL to reach full maturity and implementation feasibility. From this point, the next level, TRL 5, would involve testing in a relevant environment to simulate actual usage conditions. Progress continues until TRL 9 is reached, which corresponds to the technology being fully developed, tested and ready for commercial deployment or intensive application.

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 - Ana Teresa González Pérez
Collaborators
COLLABORATORS
Ana Teresa González Pérez

How does it work?

Our innovation focuses on sustainable agriculture in the Canary Islands, addressing challenges such as drought, wildfires, and other hazards. By collecting and sharing environmental, agronomic, economic, and social data through advanced technologies like drone sensors, we aim to restore topsoil, manage drinking water, reduce GHG emissions, and protect biodiversity. This approach helps optimize resource use, improve soil health, and engage local communities in sustainable practices, ensuring agriculture remains viable and profitable while adapting to climate change.

It is developed independently, based on the technical experience (in various areas of the remote sensing environment) of the human team that is part of the project, and the management experience of the new incorporations. We have been working for years in the capture of data with drones and different sensors, as well as training in the treatment of this data and its subsequent processing; this is why we are taking this step, trying to get more out of the information we already work with, adding value to the experience we have acquired.

Until now, the regulations have been the only limitation we have had when it comes to flying in some areas of our island territory. With the latest modification of these regulations, we are allowed to fly in all areas, provided that the necessary permits are obtained in advance. The weather is in any case the only limiting factor but taking into account that the islands enjoy good weather practically all year round, in this aspect, the trade winds would be our only limitation. Working with data from specific study areas, the whole process is generated independently for each location, from data collection, through processing and generation of models applicable to each case, and all this independently of the study areas (location, ownership, surface, boundaries, orography, …) and climatology. The primary sector is the most important sector for the development of a rural community. Everything that represents progress in this area will have an impact on the other sectors.

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