Recently, water systems have been declared critical infrastructure, and water scarcity has become a rising issue. Most water systems are controlled reactively on a plant-by-plant basis. In the hunt to make multiple remote facilities operate as one cohesive unit, many companies are offering AI, or artificial intelligence, to operate the system. Unfortunately, when it comes to techlogy, we sometimes get carried away with the velty of it without answering key questions. In this presentation, a fundamental explanation of what AI or machine learning is will be covered, as well as prerequisites for using systems of this nature. You will understand where your SCADA (Supervisory Control and Data Acquisition) systems fit into the level of control. Do you have eugh data points for training systems of this nature? Do you have the right data points for these systems? We will also touch on some shortcomings of AI systems and work to address them. For example, what happens to a data-driven system if points are lost? How does the system handle a fault or failure of a device? After this session, participants will be able to:
• Assess AI and machine learning systems.
• Evaluate the requirements for a successful AI-controlled SCADA system.
• Realize some of the shortcomings of the systems and how to possibly deal with them.

Contributor/Source

David Williams

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