PSA - Perform a Study of the Potential Benefits to Deploy the BLU-X Treatment Discovery Project for SB WWTP - EmNet LLC

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2. Conduct an in -person workshop. A meeting at the WWTP including a facilities tour and workshop with selected staff to confirm project needs and objectives will be conducted. A recap of the findings and documented opportunities will be shared during the in -person workshop. 3. Understand plant treatment process. Review documentation to understand treatment processes at the plant that are identified for evaluation. EmNet will also evaluate the current efficiency of the treatment process. 4. Develop basic model. Develop a preliminary training of the neural network embedded model based on the available data and project goals. In addition, the team will train the neural network model and perform validation to determine its precision. A sensitivity analysis will also be conducted to discern the usefulness of the model. 5. Preliminary review of model integration into BLU-X. A review of the BLU-X model versus the available plant data will be performed to analyze the benefits of implementing BLU-X at full scale and potential plant savings. 6. Implementation Plan (Phase 2). Develop a high-level implementation plan for Phase 2: BLU-X Implementation 7. Conduct Discovery Phase workshop. Hold a final in -person workshop to present the results of the preliminary review of modeling at the South Bend WWTP. This offers the opportunity for feedback, and additional plant information will be collected during the meeting to further refine the strategy. Phase 2 Implementation Feasibility: Should the project progress to Phase 2: BLU-X Implementation, EmNet will complete the following scope of work in three stages which will be highlighted in the Phase 2 Implementation Plan: 1. Turn on the LightsTM: Existing streams of data from hardware sensors in the treatment process, as well as SCADA, will be leveraged to map the available variables and generate real time information via analytics and visualization applications. Further virtual sensors will also be developed to substitute in areas where hardware sensors may not be situated. 2. Create Digital Twin: An optimized treatment process model will be developed with predictions of optimal operating parameters for various processes in the plant based on real time sensor data. 3. Optimize and Deliver Operational Guidance: Leveraging the sensor data and the newly developed Digital Copy of the treatment plant will enable the development of an RT-DSS. This RT-DSS will be designed to provide operational recommendations to achieve project objectives (e.g. energy savings). Page 5 of 6