The European project EDIH Datalife is nearing its end after 3 years promoting digital transformation in Galicia. Funded by the Digital Europe program, the European Union-Next Generation EU and the Recovery, Transformation and Resilience Plan; and supported by the Ministry of Industry and Tourism and EOI, the project boosted the adoption of advanced digital solutions based on Artificial Intelligence (AI), High-Performance Computing (HPC), and the Internet of Things (IoT) in companies and public administrations. EDIH DATAlife focused on the productive sectors linked to the bioeconomy and health, especially their SMEs, accompanying them in their innovation processes and betting on intelligent management of the natural resources of this region.

CiTIUS placed its capabilities at the service of EDIH DATAlife with a service portfolio based on the results of its research and its technologies closest to transfer to the productive sector.

CiTIUS conducted eleven pilots that respond to challenges posed by various SMEs to solve real problems in their projects and improve their competitiveness through the potential of different advanced digital solutions. The pilots focused on data exploitation and translated into proof of concepts that covered the application of computer vision techniques, data mining, natural language processing, or machine learning, which allowed testing proprietary technologies in specific application areas of the agro-food, forestry-wood, biotechnology, and health-care sectors.

Sea

In the marine field, CiTIUS carried out two proof of concepts of automatic identification using computer vision techniques. With the company Zoomare, specialized in the inspection of marine biodiversity, a solution was developed aimed at detecting algae species of interest for the pharmaceutical and food industry. In the case of FishFarmFeeder (Feeding Systems), dedicated to automatic feeding systems for aquaculture, artificial vision techniques allowed addressing the classification of deformities of fish raised in these facilities.

Forestry

The center tackled a service to improve the efficiency of forest management focused on biomass characterization using AI techniques applied to point clouds obtained with LiDAR sensors. The pilot was developed for the company 3edata, expert in engineering solutions for the forestry-wood value chain from the acquisition and analysis of environmental data, and sought to optimize the exploitation of data acquired by this technology to characterize vegetation swiftly and accurately. In the same field, CiTIUS is working with ASEFOR, dedicated to the digitization, traceability, and certification of forest processes, on a solution to monitor actions implemented in forest plots across the Galician territory using hyperspectral imaging.

Livestock

Another challenge addressed by CiTIUS within EDIH DATAlife is predicting the quality of Celta Pig breed animals using automatic learning and reasoning techniques. Proposed by ASOPORCEL, an association that deals with the recovery and conservation of this native Galician species, the pilot focuses on exploiting data from the phenotype and genotype of specimens that are crossed, seeking to improve product quality.

Biotechnology

In the biotechnological field, CiTIUS collaborates with Libera Bio, a biopharmaceutical company dedicated to developing innovative anticancer treatments based on nanotechnology. The pilot is developing predictive models that allow determining the parameters with the greatest impact on the formulation processes of drugs the company works on, seeking to improve their efficiency. Another SME in this sector participating in EDIH DATAlife is iBoneLab, specialized in studying the integration of biomaterials into living tissues that provides services to entities dedicated to developing biomaterials, bone substitutes, dental, and orthopedic implants. The solution is based, in this case, on the application of computer vision techniques on microtomography images of bone implants to improve the identification and quantification of biomaterials and their interaction with tissues.

Health

Three challenges were presented to CiTIUS in the health field to tackle within EDIH DATAlife. On one hand, a proof of concept was carried out with FBA Consulting (FBA Indaga Soft) focused on analyzing patient experience through NLP (Natural Language Processing) techniques applied to opinions collected in health surveys, focusing on sentiment analysis. Additionally, a pilot was developed to improve the organization of the medical scientific knowledge available to the company Dilemma Solutions to strengthen their Naevia Medical diagnostic support tool, and facilitate the potential application of Large Language Models (LLMs). Similarly, the integrated center of sports training, rehabilitation, and physiotherapy EcoSport Barbanza is being advised on the viability of an AI-based diagnostic support tool that reinforces the physical evaluations conducted on its patients.

Industrial Processes for the Primary Sector

Another challenge tackled by CiTIUS was the optimization of industrial processes aimed at the primary sector. In this case, the pilot was developed in collaboration with NM-IOT, an SME that offers digital solutions based on IoT in areas such as oceans and ports, agro-forestry, Industry 4.0, logistics, sustainability, and intelligent rural environments, focusing on the application of predictive analytics to improve the efficiency of manufacturing processes for heavy machinery in the marine and forestry sectors.

The eleven pilots facilitated that SMEs firsthand understand the potential of exploiting their data and the importance of digitizing their activity to apply appropriate and effective advanced digital solutions, aiming to optimize their processes, make more informed decisions, and ultimately increase their competitiveness. The experimentation and technology validation space opened by EDIH DATAlife allowed identifying promising solutions that will serve as a basis to scale towards real implementations, and strengthen CiTIUS's commitment to transferring their research results to their closest environment.