Deep learning-based models for environmental management: Recognizing construction, renovation, and demolition waste in-the-wild

Journal of Environmental Management, Journal Year: 2024, Volume and Issue: 351, P. 119908 - 119908

Published: Jan. 1, 2024

The construction industry generates a substantial volume of solid waste, often destinated for landfills, causing significant environmental pollution. Waste recycling is decisive in managing waste yet challenging due to labor-intensive sorting processes and the diverse forms waste. Deep learning (DL) models have made remarkable strides automating domestic recognition sorting. However, application DL recognize derived from construction, renovation, demolition (CRD) activities remains limited context-specific studies conducted previous research. This paper aims realistically capture complexity streams CRD context. study encompasses collecting annotating images real-world, uncontrolled environments. It then evaluates performance state-of-the-art automatically recognizing in-the-wild. Several pre-trained networks are utilized perform effectual feature extraction transfer during model training. results demonstrated that models, whether integrated with larger or lightweight backbone can composition in-the-wild which useful automated outcome emphasized applicability across various industrial domains, thereby contributing resource recovery encouraging management efforts.

Language: Английский

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Recent Developments in Technology for Sorting Plastic for Recycling: The Emergence of Artificial Intelligence and the Rise of the Robots

Recycling, Journal Year: 2024, Volume and Issue: 9(4), P. 59 - 59

Published: July 15, 2024

Plastics recycling is an important component of the circular economy. In mechanical recycling, recovery high-quality plastics for subsequent reprocessing requires plastic waste to be first sorted by type, color, and size. chemical certain types should removed as they negatively affect process. Such sortation objects at Materials Recovery Facilities (MRFs) relies increasingly on automated technology. Critical any sorting proper identification type. Spectroscopy used this end, augmented machine learning (ML) artificial intelligence (AI). Recent developments in application ML/AI are highlighted here, state art presented. Commercial equipment recyclables identified from a survey publicly available information. Automated equipment, ML/AI-based sorters, robotic sorters currently market evaluated regarding their sensors, capability sort plastics, primary application, throughput, accuracy. This information reflects rapid progress achieved plastics. However, film, dark comprising multiple polymers remains challenging. Improvements and/or new solutions forthcoming.

Language: Английский

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Artificial intelligence-empowered collection and characterization of microplastics: A review

Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 471, P. 134405 - 134405

Published: April 26, 2024

Language: Английский

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Catalytic pyrolysis of plastic waste using metal-incorporated activated carbons for monomer recovery and carbon nanotube synthesis

Journal of environmental chemical engineering, Journal Year: 2024, Volume and Issue: 12(2), P. 112226 - 112226

Published: Feb. 16, 2024

Language: Английский

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Evaluation of Artificial Intelligence-Based Solid Waste Segregation Technologies through Multi-Criteria Decision-Making and complex q-rung picture fuzzy Frank aggregation operators

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 133, P. 108154 - 108154

Published: March 6, 2024

Language: Английский

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Transforming waste into innovation: a review of plastic bricks as sustainable construction materials

Deleted Journal, Journal Year: 2024, Volume and Issue: 1(1)

Published: July 30, 2024

Abstract Plastic waste has become a pressing global issue, posing significant environmental challenges. As the construction industry continues to grow, there is growing need for sustainable materials that can address this problem. This review paper focuses on transformation of into innovation by exploring use plastic bricks as materials. The examines manufacturing processes, properties, benefits, challenges, case studies, and future research directions associated with bricks. It highlights potential reduce waste, carbon emissions, resource consumption. Additionally, addresses challenges related structural integrity, long-term durability, regulatory compliance, public perception. Case studies showcase successful implementations in projects, emphasizing their innovative design possibilities, cost-effectiveness, economic feasibility, notable strength. These illustrate achieve necessary strength applications, making them viable alternative traditional also discusses impact circular economy perspectives bricks, highlighting recyclability, reusability, management implications, contribution initiatives. Finally, concludes recommendations, focusing advancements techniques, enhanced performance engineering monitoring assessment. comprehensive sheds light transformative provides insights addressing

Language: Английский

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A digital twin system for Task-Replanning and Human-Robot control of robot manipulation

Advanced Engineering Informatics, Journal Year: 2024, Volume and Issue: 62, P. 102570 - 102570

Published: May 13, 2024

Language: Английский

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Study on efficient recognition and accurate localization method of waste plastic bottles based on deep learning

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103020 - 103020

Published: Jan. 1, 2025

Language: Английский

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Integrating circular economy while adopting digital twin for enhancing logistics efficiency: a hybrid Fuzzy Delphi-FUCOM based approach

International Journal of Logistics Research and Applications, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 43

Published: Jan. 18, 2025

Language: Английский

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ShARP-WasteSeg: A shape-aware approach to real-time segmentation of recyclables from cluttered construction and demolition waste

Waste Management, Journal Year: 2025, Volume and Issue: 195, P. 231 - 239

Published: Feb. 9, 2025

Language: Английский

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