| Title |
Material measurement units for a circular economy: Foundations through a review |
| ID_Doc |
5073 |
| Authors |
Zocco, F; McLoone, S; Smyth, B |
| Title |
Material measurement units for a circular economy: Foundations through a review |
| Year |
2022 |
| Published |
|
| DOI |
10.1016/j.spc.2022.05.022 |
| Abstract |
Long-term availability of minerals and industrial materials is a necessary condition for sustainable development as they are the constituents of any manufacturing product. To enhance the efficiency of material management, we define a computer-vision-enabled material measurement system and provide a review of works relevant to its development with particular emphasis on the foundations. A network of such systems for wide-area material stock monitoring is also covered. Finally, challenges and future research directions are discussed. As the first article bridging industrial ecology and advanced computer vision, this review is intended to support both research communities towards more sustainable manufacturing. (c) 2022 The Authors. Published by Elsevier Ltd on behalf of Institution of Chemical Engineers. This is an open access Keywords: article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Author Keywords |
Computer vision; Machine learning; Deep learning; Industrial ecology; Circular economy |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000819430300002 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
https://doi.org/10.1016/j.spc.2022.05.022
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