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CORDIS - Forschungsergebnisse der EU
CORDIS

Creation of the centre of excellence in smart forestry

CORDIS bietet Links zu öffentlichen Ergebnissen und Veröffentlichungen von HORIZONT-Projekten.

Links zu Ergebnissen und Veröffentlichungen von RP7-Projekten sowie Links zu einigen Typen spezifischer Ergebnisse wie Datensätzen und Software werden dynamisch von OpenAIRE abgerufen.

Leistungen

Strategy and policies for Forest 4.0 human resources (öffnet in neuem Fenster)

The Director for Human Resources (HR) will be responsible for writing the HR strategy and policies and proposing them to the GB for validation. They will include:Strategy: HR management; HR planning, i.e. planning of the recruitments based on the CoE’s operational needs; Job descriptions; Salaries and benefits, rewards and compensation; Working conditions and environment.Policies: Employee rights and responsibilities; Equal employment opportunities including gender equality; HR retention; Training and talent management; Risk management, safety, hygiene, and security; Performance management and appraisal; Mobility; Relationships with unionsThe final strategy and policies approved by the GB will be published as deliverable 2.1.

Innovation support service programme (öffnet in neuem Fenster)

A team led by the Director for Innovation, will support research teams to engage in innovation activities.. It will be composed of individuals with backgrounds in industry and the public sector who have significant experience in research and innovation funding. The team will also put an emphasis on knowledge creation between academic and businesses, and the creation and attraction of ICT business expertise, through joint infrastructure utilisation, end-user involvement in research, skills transfer through training of industrial actors.

Overall Design of the Acceleration Programme and Planning (öffnet in neuem Fenster)

Overall Design of the Acceleration Programme and Planning (M10)

CoE’s 5-year strategic plan including CoE KPIs and targets (öffnet in neuem Fenster)

D1.5: CoE’s 5-year strategic plan (M12): details roadmap towards KPIs to be reached by the end of the project, assigns respective responsibilities to newly recruited management team.

Implementation of methodological framework for research projects (öffnet in neuem Fenster)

Implementation of methodological framework for research projects (M12)

Report on development of smart forestry open data infrastructure (öffnet in neuem Fenster)

Report on development of smart forestry open data infrastructure (M12)

Infrastructure and equipment policy (öffnet in neuem Fenster)

A comprehensive policy for infrastructure and equipment management will therefore be prepared by Month 12 (deliverable 3.1) and implemented afterwards by the Director for Operations.

Dissemination and communication plan (öffnet in neuem Fenster)

An initial version of the dissemination, exploitation, and communication (DEC) plan –will be produced by M04 (deliverable 6.1). It will define the different measures to disseminate the project results, exploit them, or communicate about them. Target audiences of these measures will be described. Key performance indicators (KPIs) will be chosen, and target values defined for the first year of the project. Every year, the performance of the KPIs will be compared to the target values. Potential corrective measures will be decided for the coming year based on the performance of the previous year. These reviews and plan updates will be provided in the project progress reports by a D&C committee established on month 02. For the final review, a strategy for exploiting the project results after completion will be produced.

Veröffentlichungen

A Hybrid Machine Learning Model for Forest Wildfire Detection using Sounds (öffnet in neuem Fenster)

Autoren: Robertas Damaševičius, Rytis Maskeliunas, Ahmad Qurthobi
Veröffentlicht in: Annals of Computer Science and Information Systems, Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS), Ausgabe 39, 2024
Herausgeber: IEEE
DOI: 10.15439/2024F7263

d'Alembert Convolution for Enhanced Spatio-Temporal Analysis of Forest Ecosystems (öffnet in neuem Fenster)

Autoren: Rytis Maskeliūnas, Robertas Damaševičius
Veröffentlicht in: Annals of Computer Science and Information Systems, Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS), Ausgabe 39, 2024
Herausgeber: IEEE
DOI: 10.15439/2024F4228

Digital transformation of the future of forestry: an exploration of key concepts in the principles behind Forest 4.0. (öffnet in neuem Fenster)

Autoren: Damaševičius, Robertas, Mozgeris, Gintautas ir Maskeliūnas, Rytis
Veröffentlicht in: Frontiers in forests and global change, 2024, ISSN 2624-893X
Herausgeber: Frontiers
DOI: 10.3389/ffgc.2024.1424327

Forestry Scenario Modelling: Qualitative Analysis of User Needs in Lithuania (öffnet in neuem Fenster)

Autoren: Daiva Juknelienė, Michailas Palicinas, Jolanta Valčiukienė, Gintautas Mozgeris
Veröffentlicht in: Forests, Ausgabe 15, 2025, ISSN 1999-4907
Herausgeber: MDPI AG
DOI: 10.3390/F15030414

Sap Flow Density of the Prevailing Tree Species in a Hemiboreal Forest under Contrasting Meteorological and Growing Conditions (öffnet in neuem Fenster)

Autoren: Algirdas Augustaitis, Ainis Pivoras
Veröffentlicht in: Forests, Ausgabe 15, 2024, ISSN 1999-4907
Herausgeber: MDPI AG
DOI: 10.3390/f15071158

Enhancing Forest Security through Advanced Surveillance Applications (öffnet in neuem Fenster)

Autoren: Danny Buchman, Tomas Krilavičius, Rytis Maskeliūnas
Veröffentlicht in: Forests, Ausgabe 14, 2025, ISSN 1999-4907
Herausgeber: MDPI AG
DOI: 10.3390/F14122335

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