Smart waste classification in IoT-enabled smart cities using VGG16 and Cat Swarm Optimized random forest.
Effective waste management is becoming a crucial component of sustainable urban development as smart technologies are used by smart cities more and more. Smart trash categorization systems provided by IoT may greatly enhance garbage sorting and recycling mechanisms. In this context, this work presen...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316930 |
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| author | Akshat Gaurav Brij Bhooshan Gupta Varsha Arya Razaz Waheeb Attar Shavi Bansal Ahmed Alhomoud Kwok Tai Chui |
| author_facet | Akshat Gaurav Brij Bhooshan Gupta Varsha Arya Razaz Waheeb Attar Shavi Bansal Ahmed Alhomoud Kwok Tai Chui |
| author_sort | Akshat Gaurav |
| collection | DOAJ |
| description | Effective waste management is becoming a crucial component of sustainable urban development as smart technologies are used by smart cities more and more. Smart trash categorization systems provided by IoT may greatly enhance garbage sorting and recycling mechanisms. In this context, this work presents a waste categorization model based on transfer learning using the VGG16 model for feature extraction and a Random Forest classifier tuned by Cat Swarm Optimization (CSO). On a Kaggle garbage categorization dataset, the model outperformed conventional models like SVM, XGBoost, and logistic regression. With an accuracy of 85% and a high AUC of 0.85 the Random Forest model shows better performance in precision, recall, and F1-score as compared to standard machine learning models. |
| format | Article |
| id | doaj-art-33253abde1de4ff2b8bfce50a02fbcfe |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-33253abde1de4ff2b8bfce50a02fbcfe2025-08-20T02:15:24ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01202e031693010.1371/journal.pone.0316930Smart waste classification in IoT-enabled smart cities using VGG16 and Cat Swarm Optimized random forest.Akshat GauravBrij Bhooshan GuptaVarsha AryaRazaz Waheeb AttarShavi BansalAhmed AlhomoudKwok Tai ChuiEffective waste management is becoming a crucial component of sustainable urban development as smart technologies are used by smart cities more and more. Smart trash categorization systems provided by IoT may greatly enhance garbage sorting and recycling mechanisms. In this context, this work presents a waste categorization model based on transfer learning using the VGG16 model for feature extraction and a Random Forest classifier tuned by Cat Swarm Optimization (CSO). On a Kaggle garbage categorization dataset, the model outperformed conventional models like SVM, XGBoost, and logistic regression. With an accuracy of 85% and a high AUC of 0.85 the Random Forest model shows better performance in precision, recall, and F1-score as compared to standard machine learning models.https://doi.org/10.1371/journal.pone.0316930 |
| spellingShingle | Akshat Gaurav Brij Bhooshan Gupta Varsha Arya Razaz Waheeb Attar Shavi Bansal Ahmed Alhomoud Kwok Tai Chui Smart waste classification in IoT-enabled smart cities using VGG16 and Cat Swarm Optimized random forest. PLoS ONE |
| title | Smart waste classification in IoT-enabled smart cities using VGG16 and Cat Swarm Optimized random forest. |
| title_full | Smart waste classification in IoT-enabled smart cities using VGG16 and Cat Swarm Optimized random forest. |
| title_fullStr | Smart waste classification in IoT-enabled smart cities using VGG16 and Cat Swarm Optimized random forest. |
| title_full_unstemmed | Smart waste classification in IoT-enabled smart cities using VGG16 and Cat Swarm Optimized random forest. |
| title_short | Smart waste classification in IoT-enabled smart cities using VGG16 and Cat Swarm Optimized random forest. |
| title_sort | smart waste classification in iot enabled smart cities using vgg16 and cat swarm optimized random forest |
| url | https://doi.org/10.1371/journal.pone.0316930 |
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