Machine-learning-assisted classification of construction and demolition waste fragments using computer vision: Convolution versus extraction of selected features

Nežerka, V.; Zbíral, T.; Trejbal, J.

doi:10.1016/j.eswa.2023.121568

Cited by 7 publications

(1 citation statement)

References 58 publications

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“…A significant potential of application AI and Robot-learning technologies arises at the end of the life cycle of a building. Nežerka et al [21] harnessed these technologies to develop a machine-learning procedure for recognizing and classifying fragments of Construction and Demolition Waste (CDW). This innovation facilitates the deconstruction process, making it more efficient and streamlined.…”

Section: Artificial Intelligence and Robot Learningmentioning

confidence: 99%

Digital Technologies and Material Passports for Circularity in Buildings: An In-Depth Analysis of Current Practices and Emerging Trends

Trubina,

Leindecker,

Askar

et al. 2024

Lecture Notes in Civil Engineering

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The construction industry is undergoing a significant transformation driven by digitalization and an unwavering commitment to implementing circular economy (CE) principles and sustainability into its core practices. Emerging digital technologies (DTs), such as Material Passports (MPs), Building Information Modelling (BIM) Artificial Intelligence (AI) and Scanning technologies, Blockchain technology (BCT), the Internet of Things (IoT) stand out as pivotal tools capable of expediting the transition towards CE implementation in buildings. This study highlights the significant potential of six DTs to support CE application throughout the building lifecycle. Furthermore, it delves into the potential synergies among these diverse DTs, highlighting the additional benefits that collaboration can bring across different lifecycle stages of a building project. Particular emphasis is placed on the integration of MPs with other DTs, showing promise in assessing resource availability, volumes, and flows. This integration optimizes waste reduction and recycling plans, contributing to more precise selective and smart deconstruction planning. The combined use of DTs offers substantial benefits to stakeholders, enabling them to make informed decisions regarding maintenance and understand the current quality of specific materials. Through these means, the study aims to provide a comprehensive overview of the array of DTs propelling circular building practices. It also explores emerging trends in this dynamic field, scrutinizing the effectiveness of adopting these technologies throughout the building life cycle stages, and anticipating potential challenges these technologies may face.

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Section: Artificial Intelligence and Robot Learningmentioning

confidence: 99%