IT equipment and software for training, modeling and data analysis for flood and forest fire prevention, protection and management in project SOLVE

Bocevska, Andrijana and Nedelkovski, Igor and Markoski, Aleksandar and Kotevski, Zoran and Veljanovska, Kostandina and Ristevski, Blagoj and Savoska, Snezana (2024) IT equipment and software for training, modeling and data analysis for flood and forest fire prevention, protection and management in project SOLVE. In: 14th International conference on Applied Internet and Information Technologies (AIIT2024) November 8th 2024, 8 November, 2024, Zrenjanin, Serbia.

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Abstract

Recent disasters around the globe strongly indicate that most challenging territories for
managing floods and forest fires are the cross border ones. Various reasons (economic, social,
political, cultural) make it difficult to agree, establish and implement joint strategies and
policies dealing with climate change impacts, societies’ resilience and emergency
management. A huge identified deficit in exploitation of research and projects’ outputs to
strengthen civil protection systems exists at border areas. Available technological
advancements and innovations do not reach fire brigade, forestry and civil protection services.
This is due to lack of personnel, high rigidity in existing plans and procedures, inability to
create cross border standard operation procedures and most importantly to identify the cross
border area as a single area of intervention prior and during an emergency. Project Cross Border
Complex Floods and Forest Fires Prevention and Management (SOLVE) focuses on joint
actions for most common risks (forest fires and floods). This paper gives an overview of the
modern IT equipment and software for training, modeling and data analysis for flood and forest
fire prevention, protection and management acquired within this project. The paper also,
emphasizes future potentials of the equipment in terms of using data gathered in the project for
prediction in combination with potentials of machine learning

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Scientific Fields (Frascati) > Natural sciences > Computer and information sciences
Divisions:	Faculty of Information and Communication Technologies
Depositing User:	Prof. d-r. Andrijana Bocevska
Date Deposited:	11 Dec 2024 18:53
Last Modified:	11 Dec 2024 18:53
URI:	https://eprints.uklo.edu.mk/id/eprint/10531

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