Periodic Reporting for period 2 - AI-OBSERVER (Enhancing Earth Observation capabilities of the Eratosthenes Centre of Excellence on Disaster Risk Reduction through Artificial Intelligence)
Okres sprawozdawczy: 2024-01-01 do 2025-09-30
AI-OBSERVER project aimed to significantly strengthen and stimulate the scientific excellence and innovation capacity, as well as the research management and administrative skills of the ERATOSTHENES Centre of Excellence (ECoE), through several capacity building activities on AI for EO applications in the Disaster Risk Reduction thematic area, upgrading and modernizing its existing department of Resilient Society, as well as its research management and administration departments, and assisting the ECoE to reach its long-term objective of raised excellence on AI for EO on environmental hazards. The close and strategic partnership between the ECoE (Cyprus) and two internationally top-class leading research institutions, the German Research Centre for Artificial Intelligence from Germany and the University of Rome Tor Vergata from Italy, led to a research exploratory project on the application of AI on EO for multi-hazard (earthquakes, landslides, coastal erosion, fires, floods, and marine pollution) monitoring and assessment in Cyprus. Moreover, CELLOCK Ltd, the project’s industrial partner, led the commercialization, exploitation and product development aspects of AI-OBSERVER and its exploratory project outputs. All project outputs were disseminated and communicated to stakeholders, the research community, and the public, assisting the ECoE to accomplish its exploitation goals, that ECoE will capitalize on, long after the end of the project.
During the AI-OBSERVER project, the following deliverables were completed. The DMP (D1.1) presents the project's data management policy and describes the framework for accessing, using, and re-using data generated and collected. The Risk assessment and contingency plan (D1.2) describes potential risks and the corresponding mitigation actions, that will be systematically updated until the end of the project. The Quality Assurance plan (D1.3) outlined procedures for maintaining quality throughout the project, and specifying implementation procedures, including guidelines for personnel, research, data management, and communication. D2.1 provided an extensive state-of-the-art review on the current and emerging trends in AI to identify the best practices for the integration of AI with the research area of Disaster Risk Reduction (DRR) of the ECoE. D2.2 presented a database that contains potential stakeholders in the thematic area of EO for DRR using AI, with 267 organizations found relevant to the research theme categories. Α Strategic collaboration plan and five-year implementation roadmap for future collaborations (D2.3) aimed to establish research ties with the identified stakeholders, transforming them into potential partners for funding prospects and knowledge transfer activities. D3.1 assessed the current status of the ECoE in terms of scientific excellence and innovation capacity, that concluded with a SWOT analysis. A Gap analysis (D3.2) was also performed to identify the ECoE’s staff needs and the activities necessary for capacity building after the integration of advanced Al technologies in their DRR related EO activities. The target position was to establish ECoE as a key player in the integrated area of EO using AI technologies, which is presupposed that ECoE is viable and sustainable in the long term.
Moreover, 23 capacity building and knowledge transfer activities took place in the context of WP4. DFKI and UNITOV organized and carried out 6 AI-related workshops (AI-WS1-6), 4 AI-related webinars (AI-WEB1-4), 3 short-term staff exchange (SSE1-3), 2 summer schools (AI-JSS1-2), 2 expert visits (AI-EV1-2); and 1 workshop (RMA-WS), 4 webinars (RMA-WEB1-4) and 1 Expert Visit (RMA-EV1) on Research Management and Administration (RMA). These provided useful knowledge and skills towards achieving the project's goals to strengthen the scientific excellence and innovation capacity of ECoE on EO through AI, increase the inwards and outwards mobility of qualified scientists, and enhance the RMA skills of the ECoE staff. The presentations, training material and recordings from all capacity building activities are stored in a dedicated Microsoft SharePoint, as a source of knowledge that is systematically exploited by ERATOSTHENES CoE staff. The WP4 related materials, results and outputs are documented in D4.1 D4.2 D4.3 and D4.4.
The knowledge transferred by the advance partners to ERATOSTHENES CoE personnel was applied and showcased in a research exploratory project with the end-result being the development of six risk assessment/monitoring models for earthquakes, landslides, coastal erosion, fires, floods and marine pollution, using AI and EO (D5.3). Among other steps, the collection of user requirements and data for the development of these models (D5.1) the development of the Big Data Management platform (D5.2) to visualize the models' outputs, and the roadmap towards commercialization (D5.4) that set the foundation and steps that need to be taken for the commercialization of the AI-OBSERVER project's products, were also conducted.
Moreover, 23 capacity building and knowledge transfer activities took place in the context of WP4. DFKI and UNITOV organized and carried out 6 AI-related workshops (AI-WS1-6), 4 AI-related webinars (AI-WEB1-4), 3 short-term staff exchange (SSE1-3), 2 summer schools (AI-JSS1-2), 2 expert visits (AI-EV1-2); and 1 workshop (RMA-WS), 4 webinars (RMA-WEB1-4) and 1 Expert Visit (RMA-EV1) on Research Management and Administration (RMA). These provided useful knowledge and skills towards achieving the project's goals to strengthen the scientific excellence and innovation capacity of ECoE on EO through AI, increase the inwards and outwards mobility of qualified scientists, and enhance the RMA skills of the ECoE staff. The presentations, training material and recordings from all capacity building activities are stored in a dedicated Microsoft SharePoint, as a source of knowledge that is systematically exploited by ERATOSTHENES CoE staff. The WP4 related materials, results and outputs are documented in D4.1 D4.2 D4.3 and D4.4.
The knowledge transferred by the advance partners to ERATOSTHENES CoE personnel was applied and showcased in a research exploratory project with the end-result being the development of six risk assessment/monitoring models for earthquakes, landslides, coastal erosion, fires, floods and marine pollution, using AI and EO (D5.3). Among other steps, the collection of user requirements and data for the development of these models (D5.1) the development of the Big Data Management platform (D5.2) to visualize the models' outputs, and the roadmap towards commercialization (D5.4) that set the foundation and steps that need to be taken for the commercialization of the AI-OBSERVER project's products, were also conducted.
The AI-OBSERVER project is expected to have scientific (SC), economic (E), and societal impact (S), which is monitored through a set of Key Performance Indicators as follows:
- SC01: Capacity building and training activities in the form of workshops, webinars, and short staff exchanges.
- SC02: Facilitate networking with top class institutions/ stakeholders in the fields of AI and EO in the EMMENA region and beyond.
- SC03: Strengthen the research management and administration skills of the ECoE.
- E01: Creation of new research positions in the area of Artificial Intelligence for EO.
- E02: Exploitation of AI-OBSERVER results by relevant authorities/ stakeholders.
- E03: Research/ Consultancy funding.
- E04: Provision of new innovative products/services.
- S01: Raising information awareness to the public.
- S02: Raising information awareness to stakeholders, interested parties and the public.
- S03: Attracting top researchers and students in the area of Artificial Intelligence for EO.
- S04: Number of women scientists and their roles in the research.
During the project, several activities to maximize the project's impact and the further exploitation of its outcomes were carried out, such as TV/radio appearances, newspaper articles, social media posts (LinkedIn, Facebook, X), 17 meetings with stakeholders, participation in 5 networking events, public lectures, attendance at 3 European Researcher's nights, >10 submitted journal publications, >25 submitted conference publications, and attendance to 15 conferences. Moreover, through the capacity building activities carried out by the advanced partners, the impact to the project's coordinator (ECoE) and its staff is also accomplished. In this direction, other key measures to ensure further uptake and success of the project include but are not limited to: (1) the continuous engagement of stakeholders and end-users throughout the project; (2) Co-design and co-develop of the exploratory research project outputs; (3) extension of the collaboration of the coordinator with the advanced partners in terms of joint publications, research proposals and development of services. These efforts led to the development of the first AI-EO products of the ERATOSTHENES Centre of Excellence on the field of Disaster Risk Reduction and Management, focused on earthquakes, landslides, coastal erosion, fires, floods and marine pollution.
- SC01: Capacity building and training activities in the form of workshops, webinars, and short staff exchanges.
- SC02: Facilitate networking with top class institutions/ stakeholders in the fields of AI and EO in the EMMENA region and beyond.
- SC03: Strengthen the research management and administration skills of the ECoE.
- E01: Creation of new research positions in the area of Artificial Intelligence for EO.
- E02: Exploitation of AI-OBSERVER results by relevant authorities/ stakeholders.
- E03: Research/ Consultancy funding.
- E04: Provision of new innovative products/services.
- S01: Raising information awareness to the public.
- S02: Raising information awareness to stakeholders, interested parties and the public.
- S03: Attracting top researchers and students in the area of Artificial Intelligence for EO.
- S04: Number of women scientists and their roles in the research.
During the project, several activities to maximize the project's impact and the further exploitation of its outcomes were carried out, such as TV/radio appearances, newspaper articles, social media posts (LinkedIn, Facebook, X), 17 meetings with stakeholders, participation in 5 networking events, public lectures, attendance at 3 European Researcher's nights, >10 submitted journal publications, >25 submitted conference publications, and attendance to 15 conferences. Moreover, through the capacity building activities carried out by the advanced partners, the impact to the project's coordinator (ECoE) and its staff is also accomplished. In this direction, other key measures to ensure further uptake and success of the project include but are not limited to: (1) the continuous engagement of stakeholders and end-users throughout the project; (2) Co-design and co-develop of the exploratory research project outputs; (3) extension of the collaboration of the coordinator with the advanced partners in terms of joint publications, research proposals and development of services. These efforts led to the development of the first AI-EO products of the ERATOSTHENES Centre of Excellence on the field of Disaster Risk Reduction and Management, focused on earthquakes, landslides, coastal erosion, fires, floods and marine pollution.