Ethoflow: Computer Vision and Artificial Intelligence-Based Software for Automatic Behavior Analysis
Manual monitoring of animal behavior is time-consuming and prone to bias. An alternative to such limitations is using computational resources in behavioral assessments, such as tracking systems, to facilitate accurate and long-term evaluations. There is a demand for robust software that addresses an...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-05-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/9/3237 |
| _version_ | 1797534980742578176 |
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| author | Rodrigo Cupertino Bernardes Maria Augusta Pereira Lima Raul Narciso Carvalho Guedes Clíssia Barboza da Silva Gustavo Ferreira Martins |
| author_facet | Rodrigo Cupertino Bernardes Maria Augusta Pereira Lima Raul Narciso Carvalho Guedes Clíssia Barboza da Silva Gustavo Ferreira Martins |
| author_sort | Rodrigo Cupertino Bernardes |
| collection | DOAJ |
| description | Manual monitoring of animal behavior is time-consuming and prone to bias. An alternative to such limitations is using computational resources in behavioral assessments, such as tracking systems, to facilitate accurate and long-term evaluations. There is a demand for robust software that addresses analysis in heterogeneous environments (such as in field conditions) and evaluates multiple individuals in groups while maintaining their identities. The Ethoflow software was developed using computer vision and artificial intelligence (AI) tools to monitor various behavioral parameters automatically. An object detection algorithm based on instance segmentation was implemented, allowing behavior monitoring in the field under heterogeneous environments. Moreover, a convolutional neural network was implemented to assess complex behaviors expanding behavior analyses’ possibilities. The heuristics used to generate training data for the AI models automatically are described, and the models trained with these datasets exhibited high accuracy in detecting individuals in heterogeneous environments and assessing complex behavior. Ethoflow was employed for kinematic assessments and to detect trophallaxis in social bees. The software was developed in desktop applications and had a graphical user interface. In the Ethoflow algorithm, the processing with AI is separate from the other modules, facilitating measurements on an ordinary computer and complex behavior assessing on machines with graphics processing units. Ethoflow is a useful support tool for applications in biology and related fields. |
| first_indexed | 2024-03-10T11:38:10Z |
| format | Article |
| id | doaj.art-0c6a98bd9f5a40a2978c07545cfae1fb |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T11:38:10Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0c6a98bd9f5a40a2978c07545cfae1fb2023-11-21T18:41:18ZengMDPI AGSensors1424-82202021-05-01219323710.3390/s21093237Ethoflow: Computer Vision and Artificial Intelligence-Based Software for Automatic Behavior AnalysisRodrigo Cupertino Bernardes0Maria Augusta Pereira Lima1Raul Narciso Carvalho Guedes2Clíssia Barboza da Silva3Gustavo Ferreira Martins4Department of Entomology, Federal University of Viçosa, Viçosa 36570-900, MG, BrazilDepartment of Animal Biology, Federal University of Viçosa, Viçosa 36570-900, MG, BrazilDepartment of Entomology, Federal University of Viçosa, Viçosa 36570-900, MG, BrazilLaboratory of Radiobiology and Environment, University of São Paulo-Center for Nuclear Energy in Agriculture, 303 Centenário Avenue, Piracicaba 13416-000, SP, BrazilDepartment of General Biology, Federal University of Viçosa, Viçosa 36570-900, MG, BrazilManual monitoring of animal behavior is time-consuming and prone to bias. An alternative to such limitations is using computational resources in behavioral assessments, such as tracking systems, to facilitate accurate and long-term evaluations. There is a demand for robust software that addresses analysis in heterogeneous environments (such as in field conditions) and evaluates multiple individuals in groups while maintaining their identities. The Ethoflow software was developed using computer vision and artificial intelligence (AI) tools to monitor various behavioral parameters automatically. An object detection algorithm based on instance segmentation was implemented, allowing behavior monitoring in the field under heterogeneous environments. Moreover, a convolutional neural network was implemented to assess complex behaviors expanding behavior analyses’ possibilities. The heuristics used to generate training data for the AI models automatically are described, and the models trained with these datasets exhibited high accuracy in detecting individuals in heterogeneous environments and assessing complex behavior. Ethoflow was employed for kinematic assessments and to detect trophallaxis in social bees. The software was developed in desktop applications and had a graphical user interface. In the Ethoflow algorithm, the processing with AI is separate from the other modules, facilitating measurements on an ordinary computer and complex behavior assessing on machines with graphics processing units. Ethoflow is a useful support tool for applications in biology and related fields.https://www.mdpi.com/1424-8220/21/9/3237animal monitoringconvolutional neural networksdeep learningmachine learningobject detectiontracking |
| spellingShingle | Rodrigo Cupertino Bernardes Maria Augusta Pereira Lima Raul Narciso Carvalho Guedes Clíssia Barboza da Silva Gustavo Ferreira Martins Ethoflow: Computer Vision and Artificial Intelligence-Based Software for Automatic Behavior Analysis Sensors animal monitoring convolutional neural networks deep learning machine learning object detection tracking |
| title | Ethoflow: Computer Vision and Artificial Intelligence-Based Software for Automatic Behavior Analysis |
| title_full | Ethoflow: Computer Vision and Artificial Intelligence-Based Software for Automatic Behavior Analysis |
| title_fullStr | Ethoflow: Computer Vision and Artificial Intelligence-Based Software for Automatic Behavior Analysis |
| title_full_unstemmed | Ethoflow: Computer Vision and Artificial Intelligence-Based Software for Automatic Behavior Analysis |
| title_short | Ethoflow: Computer Vision and Artificial Intelligence-Based Software for Automatic Behavior Analysis |
| title_sort | ethoflow computer vision and artificial intelligence based software for automatic behavior analysis |
| topic | animal monitoring convolutional neural networks deep learning machine learning object detection tracking |
| url | https://www.mdpi.com/1424-8220/21/9/3237 |
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