In this learning module, case studies on real world applications will be presented to provide an overview of tools and methodologies for performing advanced data analysis. These solutions and ideas are examples of the next generation of data analytics, including artificial intelligence, machine learning, modeling, and other tools. Thanks to breakthroughs in computing and communication technologies, artificial intelligence and machine learning tools are available at low cost. However, real world experience is showing that implementing these tools is not as simple as “just give me the data”. Process knowledge and experience are still very useful tools in our IOT world. This module will help you see the strategies and lessons learned from others in this next generation overview.
At the conclusion of this learning module, participants will be able to
- describe effective applications of data-driven methods to water resource recovery facility projects;
- explain how applied methods are only as good as the data that are organized, formatted, and modelled appropriately;
- evaluate whether investing in large-scale sensor networks and data-driven models is the right choice for operation and management of water resource recovery facilities;
- recognize the importance of operator experience and process knowledge in IOT applications;
- use a model comparison to list merits in deploying a data-driven estimation of a model compared to a mechanistic model without any data;
- explain the process of a data management upgrade, including possible unintentional consequences and ways to eliminates these for more effective utility management; and
- give an example of a software sensor based on a neural network model.
