Implementation

aiWATERS Framework

Successful implementation of AI in the water sector requires the utilities to work on the 7 pillars. A brief description of the 7 pillars is provided below:

1. The first pillar of understanding AI and its benefits focuses on briefly explaining the different foundational concepts of AI like its main characteristics and techniques. These concepts are important for water managers and AI developers in utilities to consider. The information provided for this pillar is not exhaustive and interested readers may need to look at other literature for specific topics.

2. The second AI application goals pillar describes how AI should be applied and discusses topics like the application at different levels of the studied system, how to deploy AI in various categories, and the different modes of building AI.

3. The third pillar of data readiness describes how to evaluate the quality and quantity of collected data and how to preprocess to prepare AI-ready data.

4. The fourth pillar of knowledge integration explains how the knowledge in the minds of utility experts can be integrated into AI modeling frameworks to build more robust models.

5. The fifth pillar of model development discusses how to develop accurate and reliable AI models.

6. The sixth pillar of decision support explains methods to improve the trustworthiness of AI models and how to develop ‘human-in-the-loop’ models.

7. The seventh pillar on AI implementation explains methods for ensuring successful AI applications in the real-world and continual improvement of models.