TED4LAT ongoing research projects

Concepts: 
- Discussion in the context of the Horizon Europe project application Wellbeing concept.
- We chose as the most suitable from the list of proposed projects:Circular bioeconomy start-up villages (CSA) Call Circular economy and bioeconomy sectors (HORIZON-CL6-2024-CIRCBIO-01) (Deadline date 22 February 2024 17:00:00 Brussels time).

Project results are expected to contribute to all of the following expected outcomes:
- Development and transfer of the concept of sustainable circular bioeconomy solutions in start-up villages;
- Showcased novel governance and business models for circular systemic bioeconomy solutions in start-up villages or their groupings;
- Strengthened position of bioeconomy start-ups in rural innovation ecosystems for the development of new value-added products, technologies and approaches;
- Enhanced training opportunities and knowledge exchange and cooperation among rural innovators;
- Improved rural innovation ecosystems to build a sustainable bioeconomy within ecological boundaries based on local resources, in particular contributing to climate and biodiversity policies and targets.

Ideas:
Team decided that while preparing a systematic review on well-being, we will pay attention to the keywords of this project - sustainable circular bioeconomy, bioeconomy start-ups, start-up villages.
To look at project goals from the point of view of human and environmental well-being and their mutual interaction.

Concepts: Discussion regarding new project proposal for MSCA action for further development of research direction.

Ideas:
Joint doctorate
Joint post-doctoral research
Main idea
Continue to work on research activities with new doctoral students in the field of socio-technical systems engineering.
There are two possible directions for project proposals: *) data integration from various data bases; *) development of new algorithms of remote sensing data application for simulation modelling in the crop production.

The aim of Case is to develop an AI-based solution for remote sensing data collection, integration, and analysis for the phenotyping of cereals (winter and spring wheat, oats, spring barley) in order to provide yield potential and protein formation forecast/prediction in different growth stages throughout the season.

There are three main challenges for this case:
1. Phenotypic variation, dynamic simulation for prediction of grain yield and protein content in cereals (winter and spring wheat, oats, barley) by the integration of remote sensing data from satellite and unmanned area vehicles (UAV).
 2. Data Integration and Fusion from multiple remote sensing sources (e.g., satellites, drones) with ground truth measurements and other environmental.  Challenges is in data compatibility, quality assurance, and spatial-temporal alignment.
 3. Calibration and validation of remote sensing-derived phenotypic data against ground truth measurements collected through traditional field sampling methods. Conducting validation studies can be resource-intensive and may require careful experimental design to account for spatial and temporal variability. Data collection from unmanned area vehicles (UAV) is time and resource consuming, and data processing manually requires a lot of time and can mainly be done during the post-season time. The requirement for the case is online or on-site data processing that can give results already in on the field or the next day. Our project aims to leverage modern remote sensing technology and advanced data analysis methods to transform the phenotyping of cereal crops in new level of data processing and dynamic modelling.

Call ID
HORIZON-TMA-MSCA-DN HORIZON TMA MSCA Doctoral Networks
DL for submission:
27.11.2024 (Open – 29.05.2024.)

Concepts: 
New research paper on Digital Twin concept application for smart agriculture by the application of remote sensing data.

Ideas:
Digital Twin concept
Soil as basic factor for dynamics
Dynamic modelling and remote sensing technologies for digital twin development

Main idea:
Development time and precision are challenging factors for simulation modelling software solutions in the agricultural field. Traditionally, simulation models are designed within the communities of researchers from a particular field and are based on large data sets of historical data and knowledge. The digital transformation area provides new horizons for dynamic modelling in all sectors. Development of real-time simulation modelling environments in agriculture, environment and medicine is challenging because of timely changing objects as lining organisms or human beings. Information systems design and simulation modelling were separate disciplines in times before the Internet of Things (IoT) and new sensing technologies became available for various applications in research, production, and people’s everyday lives. The idea of the paper is to show aspects of dynamic modelling that must be considered for developing of digital twin.

Outcome:
An outcome of the workshop is the next steps for the teams in the project proposal development and directions for the new research paper.

Concepts: 
GIS, AI and Digital Twin for environmental modelling

Ideas:
Geographical Information Systems
AI for Environmental modelling
Modelling environment in the area of digital transformation
IoT data for simulation modelling (challenges and opportunities)

Main idea:
Traditionally, simulation models are designed within the communities of researchers from a particular field and are based on large data sets of historical data and knowledge. The digital transformation area provides new horizons for dynamic modelling in all sectors. Development of real-time simulation modelling environments in agriculture, environment and medicine is challenging because of timely changing objects as lining organisms or human beings. Information systems design and simulation modelling were separate disciplines in times before the Internet of Things (IoT) and new sensing technologies became available for various applications in research, production, and people’s everyday lives. The idea of the discussion is to analyse and agree on aspects for dynamic modelling that must be considered for developing of AI based digital twin.

Outcome:
An outcome of the discussion is the next steps development of new research paper.