Artificial intelligence, machine learning and GIS in environmental engineering: current trends
The use of computational tools, such as Artificial Intelligence, Machine Learning or Geographic Information Systems, has had a significant impact on the knowledge generated on environmental issues in recent years. The number of publications shown in this preliminary review of the IEEE Xplore Digi...
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| Format: | Article |
| Language: | English |
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Instituto Tecnológico de Costa Rica
2024-09-01
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| Series: | Tecnología en Marcha |
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| Online Access: | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/7304 |
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| author | Laura Hernández-Alpízar José Andrés Gómez-Mejía María Belén Argüello-Vega |
| author_facet | Laura Hernández-Alpízar José Andrés Gómez-Mejía María Belén Argüello-Vega |
| author_sort | Laura Hernández-Alpízar |
| collection | DOAJ |
| description | The use of computational tools, such as Artificial Intelligence, Machine Learning or Geographic
Information Systems, has had a significant impact on the knowledge generated on environmental
issues in recent years. The number of publications shown in this preliminary review of the IEEE
Xplore Digital Library database shows its broad applicability and scientific relevance. Search
filters and keywords such as water, air, soil, climate change, energy and waste were used. The
data obtained was processed to visualize the proportion of use in key topics of environmental
interest, giving scientific guidance towards the sites of greatest applicability, as well as towards
areas that deserve to be reinforced. In this way, this work aims to promote the development of
collaborative work solutions in the related areas of environmental and computational engineering. |
| format | Article |
| id | doaj-art-4d4e75646cf845b492fbfa01db0fa06b |
| institution | DOAJ |
| issn | 0379-3982 2215-3241 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Instituto Tecnológico de Costa Rica |
| record_format | Article |
| series | Tecnología en Marcha |
| spelling | doaj-art-4d4e75646cf845b492fbfa01db0fa06b2025-08-20T03:19:32ZengInstituto Tecnológico de Costa RicaTecnología en Marcha0379-39822215-32412024-09-01ág 879610.18845/tm.v37i7.73046590Artificial intelligence, machine learning and GIS in environmental engineering: current trendsLaura Hernández-Alpízar0https://orcid.org/0000-0002-9193-8429José Andrés Gómez-Mejía1https://orcid.org/0009-0005-1769-7283María Belén Argüello-Vega2https://orcid.org/0009-0006-1224-2658Instituto tecnológico de Costa RicaInstituto tecnológico de Costa RicaInstituto tecnológico de Costa RicaThe use of computational tools, such as Artificial Intelligence, Machine Learning or Geographic Information Systems, has had a significant impact on the knowledge generated on environmental issues in recent years. The number of publications shown in this preliminary review of the IEEE Xplore Digital Library database shows its broad applicability and scientific relevance. Search filters and keywords such as water, air, soil, climate change, energy and waste were used. The data obtained was processed to visualize the proportion of use in key topics of environmental interest, giving scientific guidance towards the sites of greatest applicability, as well as towards areas that deserve to be reinforced. In this way, this work aims to promote the development of collaborative work solutions in the related areas of environmental and computational engineering.https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/7304computational toolsdatabasewaterenergyairsolutions |
| spellingShingle | Laura Hernández-Alpízar José Andrés Gómez-Mejía María Belén Argüello-Vega Artificial intelligence, machine learning and GIS in environmental engineering: current trends Tecnología en Marcha computational tools database water energy air solutions |
| title | Artificial intelligence, machine learning and GIS in environmental engineering: current trends |
| title_full | Artificial intelligence, machine learning and GIS in environmental engineering: current trends |
| title_fullStr | Artificial intelligence, machine learning and GIS in environmental engineering: current trends |
| title_full_unstemmed | Artificial intelligence, machine learning and GIS in environmental engineering: current trends |
| title_short | Artificial intelligence, machine learning and GIS in environmental engineering: current trends |
| title_sort | artificial intelligence machine learning and gis in environmental engineering current trends |
| topic | computational tools database water energy air solutions |
| url | https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/7304 |
| work_keys_str_mv | AT laurahernandezalpizar artificialintelligencemachinelearningandgisinenvironmentalengineeringcurrenttrends AT joseandresgomezmejia artificialintelligencemachinelearningandgisinenvironmentalengineeringcurrenttrends AT mariabelenarguellovega artificialintelligencemachinelearningandgisinenvironmentalengineeringcurrenttrends |