ACWA-Data

Virginia Tech's A3 lab's ACWA datasets (AI & Cyber for Water & Agriculture)

The ACWA lab is a cyber-physical testbed comprising a cluster of computational resources, CPUs, GPUs, sensors, water tanks, pumps, valves, pipes, and soil beds. The main goal of the ACWA lab is to address pressing challenges in the water and agricultural domains by utilizing cutting-edge AI and cyber technologies.

Using the Data

To use this data, you implicitly agree, understand, and pledge to the following 5 aspects:
1- Cite the arXiv paper as well as the dataset, using the references information below.
2- Emailing our team, and notifying us of using the data, at this email address: batarseh@vt.edu
3- Pledge to not introduce intentional bias or add fake/incorrect data rows for your experiment or in your publication.
4- For access or usage of other datasets in our repository, or to request more time frequencies and/or more variables, please contact our team, at: batarseh@vt.edu
5- Use the ACWA data within the ethical considerations of our domain, including validation and trustworthiness. Refer to this publication for overall best practices in AI assurance: https://journalofbigdata.springeropen.com/articles/10.1186/s40537-021-00445-7

Thanks and regards,
The ACWA Team.
For more on the ACWA lab, please refer to: https://ai.bse.vt.edu/ACWA_Lab.html

Citation

APA Paper(s) and Data

(a1) Batarseh, F., Kulkarni, A., Sreng, C., Lin. J., and Maksud, S., "ACWA: an AI-driven cyber-physical testbed for intelligent water systems", 2023, arXiv: 2310.17654.
(a2) Batarseh, F., Kulkarni, A., Sreng, C., Lin. J., and Maksud, S., "acwa: an ai-driven cyber-physical testbed for intelligent water systems", 2023, IWA Water Practice & Technology, doi: 10.2166/wpt.2023.197
(b) Batarseh, F., Kulkarni, A., Sreng, C., Lin. J., and Maksud, S., "ACWA Data", available via GitHub at: https://github.com/AI-VTRC/ACWA-Data.

BibTex Paper IWA version

@article{IWA_ACWA_paper,
title={ACWA: an AI-driven cyber-physical testbed for intelligent water systems},
author={Batarseh, Feras and Kulkarni, Ajay and Sreng, Chhayly and Lin, Justice and Maksud, Siam},
journal={Water Practice \& Technology},
doi={10.2166/wpt.2023.197},
year={2023},
publisher={IWA Publishing}
}

BibTex Paper arXiv version

@article{ACWA_paper,
author = {Batarseh, F., Kulkarni, A., Sreng, C., Lin. J., Maksud, S.},
title = {ACWA: an AI-driven cyber-physical testbed for intelligent water systems},
year = {2023},
url = {https://arxiv.org/abs/2310.17654}
publisher = {arXiv: 2310.17654}
}

BibTex Data

@misc{ACWA_data,
author = {Batarseh, F., Kulkarni, A., Sreng, C., Lin. J., Maksud, S.},
title = {ACWA Data},
year = {2023},
publisher = {A3 Lab},
url = {https://github.com/AI-VTRC/ACWA-Data}
}