| Title |
OpenWasteAI-Open Data, IoT, and AI for Circular Economy and Waste Tracking in Resource-Constrained Communities |
| ID_Doc |
27868 |
| Authors |
Shennib, F; Eicker, U; Schmitt, K |
| Title |
OpenWasteAI-Open Data, IoT, and AI for Circular Economy and Waste Tracking in Resource-Constrained Communities |
| Year |
2024 |
| Published |
Ieee Technology And Society Magazine, 43.0, 1 |
| DOI |
10.1109/MTS.2024.3372610 |
| Abstract |
In this Article, we will introduce several interrelated problems present in municipal solid waste recycling efforts, both globally and locally. The introduction serves to demonstrate how the lack of adequate global waste tracking and community-level waste contamination are related issues. This article elaborates on how these issues could be addressed with the Internet of Things (IoT), artificial intelligence (AI), and open data technology deployment. We will investigate the existing and possible applicability of this solution in resource-constrained environments, as opposed to exclusive use in the typical "smart city" context. Finally, we will discuss the risks and limitations of this approach. |
| Author Keywords |
Waste management; Waste materials; Smart cities; Recycling; Internet of Things; Artificial intelligence; Open data; Biological system modeling; Computational modeling; Sustainable development; Predictive models; Resource management |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:001201838200011 |
| WoS Category |
Engineering, Electrical & Electronic |
| Research Area |
Engineering |
| PDF |
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