Challenges and Opportunities for Adopting Digital Twins in the Water Treatment Industry

A digital twin (DT) is a system-of-systems that extends well beyond conventional computer-based simulations and analyses. It is the conversion of every component, procedure, dynamic, and programming of a physical system, such as water treatment (WT), into a digital version. The digital and physical networks coexist harmoniously side by side, integrating all inputs and processes through real-time data transmission and communications. Water treatment system testing and analyses are made possible by the DT, which is not possible with conventional simulations or modular assessments. The complexity in successful communication and data collection, the insufficient amount of data to train Machine Learning (ML) models, the shortages of processing power required for high-quality twins, the necessity of multidisciplinary teamwork, and the lack of conventional development methodologies and validation measures are just a few of the difficulties facing the development of this technology. Since DTs are still in their infancy, there is sufficient documentation. Adopting digital twins in the water treatment industry poses challenges related to data integration, model complexity, cybersecurity, and interoperability. It also offers significant opportunities for optimizing operations, improving efficiency, enhancing decision-making, and fostering innovation across the water treatment sector.