Leveraging the internet of things, remote sensing, and artificial intelligence for sustainable forest management

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dc.contributor.authorAli, Guma
dc.contributor.authorMijwil, Maad M.
dc.contributor.authorAdamopoulos, Ioannis
dc.contributor.authorAyad, Jenan
dc.date.accessioned2025-12-12T09:46:38Z
dc.date.available2025-12-12T09:46:38Z
dc.date.issued2025-01-17
dc.description.abstractSustainable forest management is vital for addressing climate change, biodiversity loss, and deforestation. Human-induced stresses on forest ecosystems demand innovative approaches to ensure long-term health and productivity. This study explores how cutting-edge technologies, including the Internet of Things (IoT), remote sensing, and artificial intelligence (AI), enhance sustainable forest management practices. Researchers reviewed 196 studies published between 2021 and 2024 from IEEE Xplore Digital Library, MDPI, Taylor & Francis, ScienceDirect, Frontiers, Springer, SAGE, Hindawi, Nature, Wiley Online Library, and Google Scholar. The findings highlight IoT devices like drones, enabling real-time data collection on temperature, humidity, soil moisture, and tree growth, facilitating continuous forest monitoring. Remote sensing technologies, utilizing satellite imagery and aerial surveys, deliver high-resolution data for large-scale forest assessments, including forest cover changes, biomass estimation, and early detection of illegal logging. When integrated with AI, these tools enhance predictive modeling, data analysis, and decision-making, leading to more effective forest management strategies. The study also identifies challenges such as data security concerns, bandwidth limitations, interoperability issues, and high costs. Despite these barriers, IoT, remote sensing, and AI present transformative potential for improving forest resilience, carbon sequestration, and biodiversity conservation. These technologies are crucial in preserving forest ecosystems and mitigating climate change impacts by advancing real-time monitoring, optimizing resource allocation, and enabling data-driven decisions.
dc.identifier.citationAli, G., Mijwil, M. M., Adamopoulos, I., & Ayad, J. (2025). Leveraging the internet of things, remote sensing, and artificial intelligence for sustainable forest management. Babylonian Journal of Internet of Things, 2025, 1-65.
dc.identifier.issn3006-1083
dc.identifier.urihttps://dir.muni.ac.ug/handle/20.500.12260/818
dc.language.isoen
dc.publisherMesopotamian Academic Press
dc.subjectInternet of Things
dc.subjectFORESTRY, AGRICULTURAL SCIENCES and LANDSCAPE PLANNING::Area technology::Remote sensing
dc.subjectArtificial Intelligence
dc.subjectSustainable Forest Management
dc.subjectForest Monitoring
dc.titleLeveraging the internet of things, remote sensing, and artificial intelligence for sustainable forest management
dc.typeArticle

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