ACWA: An AI-driven Cyber-Physical Testbed for Intelligent Water Systems
- URL: http://arxiv.org/abs/2310.17654v1
- Date: Wed, 27 Sep 2023 00:59:52 GMT
- Title: ACWA: An AI-driven Cyber-Physical Testbed for Intelligent Water Systems
- Authors: Feras A. Batarseh, Ajay Kulkarni, Chhayly Sreng, Justice Lin, and Siam
Maksud
- Abstract summary: ACWA is motivated by the need to advance water supply management using AI and Cybersecurity experimentation.
ACWA consists of multiple topologies, sensors, computational nodes, pumps, tanks, smart water devices, as well as databases and AI models that control the system.
ACWA data are available to AI and water domain researchers and are hosted in an online public repository.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This manuscript presents a novel state-of-the-art cyber-physical water
testbed, namely: The AI and Cyber for Water and Agriculture testbed (ACWA).
ACWA is motivated by the need to advance water supply management using AI and
Cybersecurity experimentation. The main goal of ACWA is to address pressing
challenges in the water and agricultural domains by utilising cutting-edge AI
and data-driven technologies. These challenges include Cyberbiosecurity,
resources management, access to water, sustainability, and data-driven
decision-making, among others. To address such issues, ACWA consists of
multiple topologies, sensors, computational nodes, pumps, tanks, smart water
devices, as well as databases and AI models that control the system. Moreover,
we present ACWA simulator, which is a software-based water digital twin. The
simulator runs on fluid and constituent transport principles that produce
theoretical time series of a water distribution system. This creates a good
validation point for comparing the theoretical approach with real-life results
via the physical ACWA testbed. ACWA data are available to AI and water domain
researchers and are hosted in an online public repository. In this paper, the
system is introduced in detail and compared with existing water testbeds;
additionally, example use-cases are described along with novel outcomes such as
datasets, software, and AI-related scenarios.
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