| Title |
Data-driven technologies and artificial intelligence in circular economy and waste management systems: a review |
| ID_Doc |
2439 |
| Authors |
Shennib, F; Schmitt, K |
| Title |
Data-driven technologies and artificial intelligence in circular economy and waste management systems: a review |
| Year |
2021 |
| Published |
|
| DOI |
10.1109/ISTAS52410.2021.9629183 |
| Abstract |
Sustainable waste management is an objective that is far from our current reach, requiring new paradigms of thought, policy, and technology to achieve. The explosion of new applications of data-driven technologies provides the opportunity to be applied to the challenges of waste management and moving towards circular economy. This paper reviews a broad scope of current applications of data-driven and artificial intelligence in the domain of waste management, as collected from journals, reports, and a survey of business practices. We observed that few existing applications aim to make waste data openly available. Based on this gap, we propose novel areas for research and development to assess the potential of collaborative, open, data-driven circular economy initiatives. |
| Author Keywords |
waste management; circular economy; zero waste; data-driven; artificial intelligence; open data; literature review |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:000782422800057 |
| WoS Category |
Computer Science, Interdisciplinary Applications; Engineering, Multidisciplinary |
| Research Area |
Computer Science; Engineering |
| PDF |
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