ACWA: an AI-driven cyber-physical testbed for intelligent water systems

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 aim to advance water resources’ management using AI and cybersecurity experimentation. The main objective of ACWA is to address pressing challenges in the water and agricultural domains by utilis-ing 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 is built consisting of topologies, sensors, computational clusters, 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 is based on fluid and constituent transport principles that produce a theoretical time series of a water distribution system. It creates a benchmark for comparing the theoretical approach with real-life outcomes via the physical ACWA testbed. ACWA data are available to AI and water sector researchers and are hosted in an online public repository. In this paper, the system is introduced and compared with existing water testbeds; additionally, use cases are described along with novel outcomes, such as datasets, software, and AI models.