Innovative AIoT Solutions for PET Waste Collection in the Circular Economy Towards a Sustainable Future
Recycling plastic waste has emerged as one of the most pressing environmental challenges of the 21st century. One of the biggest challenges in polyethylene terephthalate (PET) recycling is the requirement to return bottles in their original, undeformed state. This necessitates storing large volumes...
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MDPI AG
2025-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/13/7353 |
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| author | Cosmina-Mihaela Rosca Adrian Stancu |
| author_facet | Cosmina-Mihaela Rosca Adrian Stancu |
| author_sort | Cosmina-Mihaela Rosca |
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| description | Recycling plastic waste has emerged as one of the most pressing environmental challenges of the 21st century. One of the biggest challenges in polyethylene terephthalate (PET) recycling is the requirement to return bottles in their original, undeformed state. This necessitates storing large volumes of waste and takes up substantial space. Therefore, this paper seeks to address this issue and introduces a novel AIoT-based infrastructure that integrates the PET Bottle Identification Algorithm (PBIA), which can accurately recognize bottles regardless of color or condition and distinguish them from other waste. A detailed study of Azure Custom Vision services for PET bottle identification is conducted, evaluating its object recognition capabilities and overall performance within an intelligent waste management framework. A key contribution of this work is the development of the Algorithm for Citizens’ Trust Level by Recycling (ACTLR), which assigns trust levels to individuals based on their recycling behavior. This paper also details the development of a cost-effective prototype of the AIoT system, demonstrating its low-cost feasibility for real-world implementation, using the Asus Tinker Board as the primary hardware. The software application is designed to monitor the collection process across multiple recycling points, offering Microsoft Azure cloud-hosted data and insights. The experimental results demonstrate the feasibility of integrating this prototype on a large scale at minimal cost. Moreover, the algorithm integrates the allocation points for proper recycling and penalizes fraudulent activities. This innovation has the potential to streamline the recycling process, reduce logistical burdens, and significantly improve public participation by making it more convenient to store and return used plastic bottles. |
| format | Article |
| id | doaj-art-6da1aa3e23b94e73a6b51eebb795a1f0 |
| institution | Matheson Library |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| series | Applied Sciences |
| spelling | doaj-art-6da1aa3e23b94e73a6b51eebb795a1f02025-07-11T14:36:25ZengMDPI AGApplied Sciences2076-34172025-06-011513735310.3390/app15137353Innovative AIoT Solutions for PET Waste Collection in the Circular Economy Towards a Sustainable FutureCosmina-Mihaela Rosca0Adrian Stancu1Department of Automatic Control, Computers, and Electronics, Faculty of Mechanical and Electrical Engineering, Petroleum-Gas University of Ploiesti, 39 Bucharest Avenue, 100680 Ploiesti, RomaniaDepartment of Business Administration, Faculty of Economic Sciences, Petroleum-Gas University of Ploiesti, 39 Bucharest Avenue, 100680 Ploiesti, RomaniaRecycling plastic waste has emerged as one of the most pressing environmental challenges of the 21st century. One of the biggest challenges in polyethylene terephthalate (PET) recycling is the requirement to return bottles in their original, undeformed state. This necessitates storing large volumes of waste and takes up substantial space. Therefore, this paper seeks to address this issue and introduces a novel AIoT-based infrastructure that integrates the PET Bottle Identification Algorithm (PBIA), which can accurately recognize bottles regardless of color or condition and distinguish them from other waste. A detailed study of Azure Custom Vision services for PET bottle identification is conducted, evaluating its object recognition capabilities and overall performance within an intelligent waste management framework. A key contribution of this work is the development of the Algorithm for Citizens’ Trust Level by Recycling (ACTLR), which assigns trust levels to individuals based on their recycling behavior. This paper also details the development of a cost-effective prototype of the AIoT system, demonstrating its low-cost feasibility for real-world implementation, using the Asus Tinker Board as the primary hardware. The software application is designed to monitor the collection process across multiple recycling points, offering Microsoft Azure cloud-hosted data and insights. The experimental results demonstrate the feasibility of integrating this prototype on a large scale at minimal cost. Moreover, the algorithm integrates the allocation points for proper recycling and penalizes fraudulent activities. This innovation has the potential to streamline the recycling process, reduce logistical burdens, and significantly improve public participation by making it more convenient to store and return used plastic bottles.https://www.mdpi.com/2076-3417/15/13/7353AIoT infrastructureAsus Thinker BoardAzure Custom VisionPET and non-PETbottle identificationplastic recycling |
| spellingShingle | Cosmina-Mihaela Rosca Adrian Stancu Innovative AIoT Solutions for PET Waste Collection in the Circular Economy Towards a Sustainable Future Applied Sciences AIoT infrastructure Asus Thinker Board Azure Custom Vision PET and non-PET bottle identification plastic recycling |
| title | Innovative AIoT Solutions for PET Waste Collection in the Circular Economy Towards a Sustainable Future |
| title_full | Innovative AIoT Solutions for PET Waste Collection in the Circular Economy Towards a Sustainable Future |
| title_fullStr | Innovative AIoT Solutions for PET Waste Collection in the Circular Economy Towards a Sustainable Future |
| title_full_unstemmed | Innovative AIoT Solutions for PET Waste Collection in the Circular Economy Towards a Sustainable Future |
| title_short | Innovative AIoT Solutions for PET Waste Collection in the Circular Economy Towards a Sustainable Future |
| title_sort | innovative aiot solutions for pet waste collection in the circular economy towards a sustainable future |
| topic | AIoT infrastructure Asus Thinker Board Azure Custom Vision PET and non-PET bottle identification plastic recycling |
| url | https://www.mdpi.com/2076-3417/15/13/7353 |
| work_keys_str_mv | AT cosminamihaelarosca innovativeaiotsolutionsforpetwastecollectioninthecirculareconomytowardsasustainablefuture AT adrianstancu innovativeaiotsolutionsforpetwastecollectioninthecirculareconomytowardsasustainablefuture |