The first phase of SCAPI, aimed at improving the competitiveness of vine tomatoes, concludes in August.

OnTech Innovation is leading the SCAPI project (Ref.: AEI-010500-2021b-21), which aims to design and build a complex agronomic sensor for precision agriculture in greenhouses. The cluster, to which Soltel belongs, was founded in 2013 and has become the largest digital economy business organization and the largest technology cluster in Andalusia. It develops several projects to improve productivity and quality of life, one of which is SCAPI. This sensor system, through non-invasive monitoring with precision at the individual plant and fruit level, provides information for optimal harvesting.

SCAPI adds artificial intelligence to the precision sensorization of greenhouses to improve all decision processes and optimize the use of resources, leading agricultural holdings to optimal performance.

The project is an initiative funded by the Ministry of Industry, Trade and Tourism, as part of the Recovery, Transformation and Resilience Plan, with Next Generation EU funds from the European Union, through support for Innovative Business Clusters aimed at improving the competitiveness of small and medium-sized enterprises. Of the total budget for this first phase, which amounts to €409,709, €321,210 has been funded, representing approximately 80 percent.

Following the design and commissioning of the sensor, the prototype will be installed in a 400-square-meter greenhouse at the Tecnova Experimental Center in Almería. The project includes the installation of climate stations and the intelligent moving structure at an optimal point within the greenhouse, as well as the machine vision camera to efficiently record images of the fruit and thus obtain the most accurate ripening results.

Soltel is handling the implementation of the software that manages data acquisition from both the machine vision camera and the environmental data within the greenhouse. Once installed, the correct communication and activation of the devices will be verified, followed by their analytical representation. All these steps will be carried out before the validation and data collection begin in the crop, ensuring the proper installation of the necessary equipment for its use. To this end, the Tecnova Experimental Center will construct a metal structure over the crop, along which the camera will slide to take daily samples from each plant.

This first phase involves the development of the sensor, called the assisted sensor, for collecting information and processing it using artificial intelligence, which will be processed as data to be provided to farmers and producers for decision-making. All of this will take place in greenhouse farms dedicated to the cultivation of vine tomatoes.

In a second phase, initially planned for 2023, the scope of SCAPI will be expanded because the results obtained with the assisted sensor will have to be integrated with the automation tools of the greenhouse operation, so that the control of irrigation, humidity and ventilation will be done directly by the system.

WATERMELON AND MELON

Finally, a third phase is planned in which the technology developed in phase 2 will be extrapolated using an autonomous sensor. This will allow its implementation in other crops, such as watermelon and melon, providing information to identify the optimal harvest time and the point at which the fruit reaches its peak quality for market. This third phase of the SCAPI project has an approximate budget of €490,000.

The project combines IoT sensors and hyperspectral camera-based sensors, Artificial Intelligence developments and Decision Support Systems, to provide a digital solution that allows for a level of accuracy previously unknown in understanding the evolution and quality of crops.

Soltel takes pride in working to improve the quality of life and profitability of farmers, the latter being a key factor for the survival of many small and medium-sized agricultural businesses. SCAPI allows for increased crop quality in greenhouses, determining the optimal ripening time, and monitoring and estimating production thanks to the automation of greenhouses and their ventilation, irrigation, and humidity control processes.