Summary of A Dataset For Research on Water Sustainability, by Pranjol Sen Gupta et al.
A Dataset for Research on Water Sustainability
by Pranjol Sen Gupta, Md Rajib Hossen, Pengfei Li, Shaolei Ren, Mohammad A. Islam
First submitted to arxiv on: 24 May 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Performance (cs.PF)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper addresses freshwater scarcity globally, which hinders research in water sustainability due to limited access to operational water footprint data. To address this, the authors create a dataset for direct and indirect water usage in cooling systems and electricity generation. The dataset comprises hourly water efficiency data from 2019-2023 for major U.S. cities and states. Additionally, the paper presents cooling system models that account for weather impacts on water efficiency. A preliminary analysis of the dataset is provided, along with three potential applications that can benefit from it. The dataset is publicly available at Open Science Framework (OSF). This study’s contribution lies in providing a valuable resource for optimizing water usage and exploring opportunities hidden within temporal and spatial variations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper helps solve a big problem: freshwater scarcity. Right now, people don’t have access to the right data to make changes to use less water. The authors fix this by creating a dataset that shows how much water is used in cooling systems and electricity generation. They also include models that show how weather affects water usage. This can help people optimize their water usage and find new ways to save water. |
