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Smart Forest Observatories Network: A MAPE-K Architecture Based Approach for Detecting and Monitoring Forest Damage
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (DISA;DISA-SIG;DISA-AdaptWise;AdaptWise)ORCID iD: 0000-0002-7555-7300
Lahore University of Management Sciences, Pakistan.
Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (Interaction Design;Linnaeus University Systems Community)ORCID iD: 0000-0003-0512-6350
2023 (English)In: Proceedings of the Conference Digital solutions for detecting and monitoring forest damage: Växjö, Sweden, March 28-29, 2023, 2023Conference paper, Poster (with or without abstract) (Other academic)
Sustainable development
SDG 13: Take urgent action to combat climate change and its impacts by regulating emissions and promoting developments in renewable energy, SDG 15: Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
Abstract [en]

Forests are essential for life, providing various ecological, social, and economic benefits worldwide. However, one of the main challenges faced by the world is the forest damage caused by biotic and abiotic factors. In any case, the forest damages threaten the environment, biodiversity, and ecosystem. Climate change and anthropogenic activities, such as illegal logging and industrial waste, are among the principal elements contributing to forest damage. To achieve the United Nations' Sustainable Development Goals (SDGs) related to forests and climate change, detecting and analyzing forest damages, and taking appropriate measures to prevent or reduce the damages are essential. To that end, we envision establishing a Smart Forest Observatories (SFOs) network, as shown below, which can be either a local area or a wide area network involving remote forests. The basic idea is to use Monitor, Analyze, Plan, Execute, and Knowledge (MAPE-K) architecture from autonomic computing and self-adaptive software systems domain to design and develop the SFOs network. The SFOs are planned to collect, analyze, and share the collected data and analysis results using state-of-the-art methods. The principal objective of the SFOs network is to provide accurate and real-time data to policymakers and forest managers, enabling them to develop effective policies and management strategies for global forest conservation that help to achieve SDGs related to forests and climate change.

Place, publisher, year, edition, pages
2023.
Keywords [en]
MAPE-K, Self-Adaptation, Forest Damage, Forest
National Category
Forest Science Agricultural Science, Forestry and Fisheries Computer Sciences Computer and Information Sciences
Research subject
Computer and Information Sciences Computer Science; Computer Science, Software Technology; Computer and Information Sciences Computer Science, Information Systems; Technology (byts ev till Engineering), Forestry and Wood Technology
Identifiers
URN: urn:nbn:se:lnu:diva-120087OAI: oai:DiVA.org:lnu-120087DiVA, id: diva2:1749459
Conference
International Conference on Digital Solutions for Detecting and Monitoring Forest Damage, Linnaeus University, Växjö, Sweden
Available from: 2023-04-06 Created: 2023-04-06 Last updated: 2023-05-26Bibliographically approved

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