A Smart Intelligence System for Hen Breed and Disease classification using Extra Tree classifier-based Ensemble Technique
Abstract This research paper probes into the vital importance of poultry farming, specifically focusing on hens, which play a vibrant role in meeting the global demand for both eggs and meat. Identifying hen breeds and recognizing diseases pose significant challenges in poultry management, necessita...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-02-01
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| Series: | Journal of Electrical Systems and Information Technology |
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| Online Access: | https://doi.org/10.1186/s43067-025-00191-3 |
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| author | Galib Muhammad Shahriar Himel Md. Masudul Islam |
| author_facet | Galib Muhammad Shahriar Himel Md. Masudul Islam |
| author_sort | Galib Muhammad Shahriar Himel |
| collection | DOAJ |
| description | Abstract This research paper probes into the vital importance of poultry farming, specifically focusing on hens, which play a vibrant role in meeting the global demand for both eggs and meat. Identifying hen breeds and recognizing diseases pose significant challenges in poultry management, necessitating innovative solutions to enhance the efficiency of farming practices. The experimental efforts of this study were centered around classifying ten distinct hen breeds and recognizing four prevalent hen diseases through the implementation of an ensemble method. Utilizing a stacking-based ensemble approach, we achieved remarkable success, achieving a test accuracy of 99.94% for both hen breeds and 99.01% for disease classification based on feces images. In this study, we employed the self-collected dataset named ‘GalliformeSpectra’ for hen breed recognition, alongside a publicly accessible dataset of feces images to identify diseases. Additionally, to facilitate practical application, we have developed a smartphone application seamlessly incorporating our model, enabling real-time hen breed and disease classification. The findings of this study represent a groundbreaking accomplishment in the realm of hen breed classification using machine learning, distinguishing this study as both state-of-the-art and pioneering. By addressing critical challenges in poultry farming, this research contributes not only to academic progress but also provides practical solutions to enhance efficiency and sustainability in the poultry industry resulting in ease the farmers to be able to plan their farming business efficiently and to take measures in the correct time in case of diseases outbreak thus contributing to farmers, communities, and researchers. |
| format | Article |
| id | doaj-art-12b0c593510f4e518b3cc6a114a8f00f |
| institution | Kabale University |
| issn | 2314-7172 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Electrical Systems and Information Technology |
| spelling | doaj-art-12b0c593510f4e518b3cc6a114a8f00f2025-02-09T12:17:04ZengSpringerOpenJournal of Electrical Systems and Information Technology2314-71722025-02-0112113210.1186/s43067-025-00191-3A Smart Intelligence System for Hen Breed and Disease classification using Extra Tree classifier-based Ensemble TechniqueGalib Muhammad Shahriar Himel0Md. Masudul Islam1School of Computer Sciences, Universiti Sains Malaysia (UMS)Department of Computer Science and Engineering, Jahangirnagar UniversityAbstract This research paper probes into the vital importance of poultry farming, specifically focusing on hens, which play a vibrant role in meeting the global demand for both eggs and meat. Identifying hen breeds and recognizing diseases pose significant challenges in poultry management, necessitating innovative solutions to enhance the efficiency of farming practices. The experimental efforts of this study were centered around classifying ten distinct hen breeds and recognizing four prevalent hen diseases through the implementation of an ensemble method. Utilizing a stacking-based ensemble approach, we achieved remarkable success, achieving a test accuracy of 99.94% for both hen breeds and 99.01% for disease classification based on feces images. In this study, we employed the self-collected dataset named ‘GalliformeSpectra’ for hen breed recognition, alongside a publicly accessible dataset of feces images to identify diseases. Additionally, to facilitate practical application, we have developed a smartphone application seamlessly incorporating our model, enabling real-time hen breed and disease classification. The findings of this study represent a groundbreaking accomplishment in the realm of hen breed classification using machine learning, distinguishing this study as both state-of-the-art and pioneering. By addressing critical challenges in poultry farming, this research contributes not only to academic progress but also provides practical solutions to enhance efficiency and sustainability in the poultry industry resulting in ease the farmers to be able to plan their farming business efficiently and to take measures in the correct time in case of diseases outbreak thus contributing to farmers, communities, and researchers.https://doi.org/10.1186/s43067-025-00191-3Computer visionHen breed classificationHen diseases classificationEnsemble learningExpert system |
| spellingShingle | Galib Muhammad Shahriar Himel Md. Masudul Islam A Smart Intelligence System for Hen Breed and Disease classification using Extra Tree classifier-based Ensemble Technique Journal of Electrical Systems and Information Technology Computer vision Hen breed classification Hen diseases classification Ensemble learning Expert system |
| title | A Smart Intelligence System for Hen Breed and Disease classification using Extra Tree classifier-based Ensemble Technique |
| title_full | A Smart Intelligence System for Hen Breed and Disease classification using Extra Tree classifier-based Ensemble Technique |
| title_fullStr | A Smart Intelligence System for Hen Breed and Disease classification using Extra Tree classifier-based Ensemble Technique |
| title_full_unstemmed | A Smart Intelligence System for Hen Breed and Disease classification using Extra Tree classifier-based Ensemble Technique |
| title_short | A Smart Intelligence System for Hen Breed and Disease classification using Extra Tree classifier-based Ensemble Technique |
| title_sort | smart intelligence system for hen breed and disease classification using extra tree classifier based ensemble technique |
| topic | Computer vision Hen breed classification Hen diseases classification Ensemble learning Expert system |
| url | https://doi.org/10.1186/s43067-025-00191-3 |
| work_keys_str_mv | AT galibmuhammadshahriarhimel asmartintelligencesystemforhenbreedanddiseaseclassificationusingextratreeclassifierbasedensembletechnique AT mdmasudulislam asmartintelligencesystemforhenbreedanddiseaseclassificationusingextratreeclassifierbasedensembletechnique AT galibmuhammadshahriarhimel smartintelligencesystemforhenbreedanddiseaseclassificationusingextratreeclassifierbasedensembletechnique AT mdmasudulislam smartintelligencesystemforhenbreedanddiseaseclassificationusingextratreeclassifierbasedensembletechnique |