Towards real-time monitoring of insect species populations
Insect biodiversity and abundance are in global decline, potentially leading to a crisis with profound ecological and economic consequences. Methods and technologies to monitor insect species to aid in preservation efforts are rapidly being developed yet their adoption has been slow and focused on s...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
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Springer Science and Business Media LLC
2024
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| Online Access: | https://hdl.handle.net/1721.1/157744 |
| _version_ | 1824458332036923392 |
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| author | Venverloo, Titus Duarte, Fábio |
| author2 | Massachusetts Institute of Technology. Department of Urban Studies and Planning |
| author_facet | Massachusetts Institute of Technology. Department of Urban Studies and Planning Venverloo, Titus Duarte, Fábio |
| author_sort | Venverloo, Titus |
| collection | MIT |
| description | Insect biodiversity and abundance are in global decline, potentially leading to a crisis with profound ecological and economic consequences. Methods and technologies to monitor insect species to aid in preservation efforts are rapidly being developed yet their adoption has been slow and focused on specific use cases. We propose a computer vision model that works towards multi-objective insect species identification in real-time and on a large scale. We leverage an image data source with 16 million instances and a recent improvement in the YOLO computer vision architecture to present a quick and open-access method to develop visual AI models to monitor insect species across climatic regions. |
| first_indexed | 2025-02-19T04:24:12Z |
| format | Article |
| id | mit-1721.1/157744 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2025-02-19T04:24:12Z |
| publishDate | 2024 |
| publisher | Springer Science and Business Media LLC |
| record_format | dspace |
| spelling | mit-1721.1/1577442025-01-03T04:23:49Z Towards real-time monitoring of insect species populations Venverloo, Titus Duarte, Fábio Massachusetts Institute of Technology. Department of Urban Studies and Planning Insect biodiversity and abundance are in global decline, potentially leading to a crisis with profound ecological and economic consequences. Methods and technologies to monitor insect species to aid in preservation efforts are rapidly being developed yet their adoption has been slow and focused on specific use cases. We propose a computer vision model that works towards multi-objective insect species identification in real-time and on a large scale. We leverage an image data source with 16 million instances and a recent improvement in the YOLO computer vision architecture to present a quick and open-access method to develop visual AI models to monitor insect species across climatic regions. 2024-12-03T18:12:46Z 2024-12-03T18:12:46Z 2024 2024-12-03T18:00:00Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/157744 Venverloo, T., Duarte, F. Towards real-time monitoring of insect species populations. Sci Rep 14, 18727 (2024). en 10.1038/s41598-024-68502-8 Scientific Reports Creative Commons Attribution-NonCommercial-NoDerivs https://creativecommons.org/licenses/by-nc-nd/4.0/ application/pdf Springer Science and Business Media LLC Springer Nature |
| spellingShingle | Venverloo, Titus Duarte, Fábio Towards real-time monitoring of insect species populations |
| title | Towards real-time monitoring of insect species populations |
| title_full | Towards real-time monitoring of insect species populations |
| title_fullStr | Towards real-time monitoring of insect species populations |
| title_full_unstemmed | Towards real-time monitoring of insect species populations |
| title_short | Towards real-time monitoring of insect species populations |
| title_sort | towards real time monitoring of insect species populations |
| url | https://hdl.handle.net/1721.1/157744 |
| work_keys_str_mv | AT venverlootitus towardsrealtimemonitoringofinsectspeciespopulations AT duartefabio towardsrealtimemonitoringofinsectspeciespopulations |