Individual wood board tracing method using oriented fast and rotated brief method in the wood traceability system

Sun, Ye; Du, Guanben; Lin, Qizhao; Zhong, Lin; Zhao, Yanjie; Qiu, Jian; Cao, Yong

doi:10.1007/s00226-022-01379-w

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…Furthermore, such properties are intrinsic to the biometric qualities of a piece of wood and are therefore not communicable to anyone else. Thus, it is viable to trace a fragment of the wood's individuality [162].…”

Section: Technologies and Software Platforms Used For Wood Traceabili...mentioning

confidence: 99%

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Timber Traceability and Sustainable Transportation Management: A Review of Technologies and Procedures

Elias

2024

FWIAFE

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There has been considerable research on sustainable forest management due to its importance in ensuring the long-term health of the forests and its industries. Traceability is an important tool to ensure that the wood and wood-based products are produced in a legal, sustainable, and ethical manner. Therefore, various technologies were implemented within the supply chain to monitor and trace the wood with the aim of fulfilling the traceability objectives. Using a systematic literature review, this paper provides a comprehensive state-of-the-art on the technologies and procedures used in timber traceability and transportation management. It debates traceability tradition and advanced methods such as smart marking, QR (Quick Response) codes, DNA fingerprinting, smartphone apps, RFID (Radio Frequency Identification), machine learning, and computer vision since these technologies enable the integrity of the supply chain by documenting the source of wood and following up on the wood in all the stages, beginning from the standing tree until the final customer. The paper also reviews the advancements in wood transportation management systems, including spatial databases, GPS (Global Positioning System), and fleet management systems, which ultimately lead to real-time monitoring and optimisation of transportation routes, leading to improved efficiency and minimal environmental impact. The review results acknowledge that financial constraints, infrastructure limitations, data management uncertainties, acceptance and compliance issues, and stakeholder commitment are still challenges to implementing traceability technology in the forestry sector. Moreover, this review not only highlights how traceability systems promote responsible forestry practices, ensure sustainable timber sourcing, and develop supply chain management, but also the advantages of utilising these technological advances at economic, social, and environmental levels.

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Section: Technologies and Software Platforms Used For Wood Traceabili...mentioning

confidence: 99%

“…It showed excellent speed and resilience, with an accuracy of 98.5 percent. Nevertheless, it bases its findings on a publicly available dataset of 2,941 images, which might not include every possible wood species [162]. DNA markers have the potential to become an important tool to trace wood [75].…”

Section: Blockchainmentioning

confidence: 99%

Timber Traceability and Sustainable Transportation Management: A Review of Technologies and Procedures

Elias

2024

FWIAFE

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Web Solution Based on QR Code for the Traceability of the Wood Transformation Process

Amaya

Rojas

Guerrero

2022

2022 IEEE XXIX International Conference on Electronics, Electrical Engineering and Computing (INTERCON)

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Automated Evaluation and Rating of Product Repairability Using Artificial Intelligence-Based Approaches

Liao,

Esmaeilian,

Behdad

2023

Journal of Manufacturing Science and Engineering

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Despite the importance of product repairability, current methods for assessing and grading repairability are limited, which hampers the efforts of designers, remanufacturers, original equipment manufacturers (OEMs), and repair shops. To improve the efficiency of assessing product repairability, this study introduces two artificial intelligence (AI) based approaches. The first approach is a supervised learning framework that utilizes object detection on product teardown images to measure repairability. Transfer learning is employed with machine learning architectures such as ConvNeXt, GoogLeNet, ResNet50, and VGG16 to evaluate repairability scores. The second approach is an unsupervised learning framework that combines feature extraction and cluster learning to identify product design features and group devices with similar designs. It utilizes an Oriented FAST and Rotated BRIEF feature extractor (ORB) along with k-means clustering to extract features from teardown images and categorize products with similar designs. To demonstrate the application of these assessment approaches, smartphones are used as a case study. The results highlight the potential of artificial intelligence in developing an automated system for assessing and rating product repairability.

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Individual wood board tracing method using oriented fast and rotated brief method in the wood traceability system

Cited by 3 publications

References 33 publications

Timber Traceability and Sustainable Transportation Management: A Review of Technologies and Procedures

Timber Traceability and Sustainable Transportation Management: A Review of Technologies and Procedures

Web Solution Based on QR Code for the Traceability of the Wood Transformation Process

Automated Evaluation and Rating of Product Repairability Using Artificial Intelligence-Based Approaches

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