| Title: | Artificial Intelligence and Environmental Challenges : Research Insights and Emerging Solutions |
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| Authors: | ID Leskovar, Robert T. (Editor) |
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| Files: |  https://press.um.si/index.php/ump/catalog/book/1132
 9789612991609.pdf (9,22 MB)
MD5: FD090F84D0266CD65308020C96DF9D84
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| Language: | English |
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| Work type: | Scientific work |
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| Typology: | 2.01 - Scientific Monograph |
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| Organization: | FOV - Faculty of Organizational Sciences in Kranj
UZUM - University of Maribor Press
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| Abstract: | This volume examines where artificial intelligence can provide genuine insight into environmental problems, and at what cost. Across eight chapters, contributors apply machine learning, deep learning, econometric modelling, and computational simulation to a range of pressing challenges: forecasting wind and solar energy output, deploying efficient AI on resource-constrained edge devices, quantifying risk in sustainable finance, detecting faults in photovoltaic installations, analysing air quality and CO₂ emissions data, simulating nanoplastic interactions with biological systems, and modelling urban heat transfer. A recurring theme is the critical importance of data quality — sparse, biased, or poorly curated datasets remain a fundamental obstacle to trustworthy modelling. The volume equally emphasises interpretability, recognising that environmental decision-making is ultimately a human and political process. Taken together, the chapters offer an honest, domain-grounded assessment of the current capabilities and limitations of AI as a tool for addressing environmental challenges. |
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| Keywords: | artificial intelligence, machine learning, environmental issues, CO2 emissions, PM2.3 particles, risk, failure, renewable energy, wind turbine, solar power plant, edge AI |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Place of publishing: | Maribor |
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| Place of performance: | Maribor |
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| Publisher: | University of Maribor, University of Maribor Press |
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| Year of publishing: | 2026 |
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| Year of performance: | 2026 |
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| PID: | 20.500.12556/DKUM-98526  |
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| ISBN: | 978-961-299-160-9 |
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| UDC: | 004.8:502.1(082)(0.034.2) |
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| COBISS.SI-ID: | 281943555 |
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| DOI: | 10.18690/um.fov.5.2026 |
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| Publication date in DKUM: | 18.06.2026 |
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| Views: | 178 |
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| Downloads: | 3 |
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| Metadata: |    |
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| Categories: | Misc.
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