Multi-Agent Automation of Wastewater Treatment Plant Incident Customer Notifications

This workflow automates a critical public safety bottleneck: the manual, high-stakes process of notifying communities during wastewater incidents like odor releases or bypass events. It eliminates the lag between SCADA alarms and public communication, directly reducing community health risk and regulatory exposure. The operational upside comes from replacing fragmented, manual callouts with a system that instantly maps incidents to GIS layers, segments affected populations from the CIS, and dispatches compliant advisories via SMS, IVR, and email channels.

Implementation integrates with plant SCADA, the customer information system (CIS), and geospatial platforms like Esri. A LangGraph orchestrator manages specialized agents for geofencing, template retrieval, and channel dispatch. Critical controls include pre-approved message libraries, mandatory human review for novel incidents, and a full audit trail for regulatory reporting. The system is deployed as a containerized service adjacent to core utility systems, with rollback protocols for message recall.

This workflow automates the critical, time-sensitive bottleneck of public notification during wastewater treatment plant incidents like odor releases or bypass events. By replacing manual monitoring, geospatial analysis, and communication drafting, it reduces public health risk exposure and operational liability. The savings come from preventing regulatory fines, lowering crisis management labor, and protecting community trust through faster, more accurate advisories. The architecture integrates real-time SCADA/PLC data, GIS systems, and multi-channel communication APIs under a central orchestrator.

Implementation centers on a LangGraph or similar orchestration framework, where specialized agents handle validation, geofencing, content generation, and dispatch. The orchestrator manages state, exception routing to a human review dashboard, and maintains a full audit trail for regulatory compliance. Key integrations include plant historian systems (e.g., OSIsoft PI), municipal GIS, and telecom APIs (Twilio, Sinch). Rollout requires phased validation against historical incident data, strict approval workflows for message templates, and real-time monitoring of delivery status and public sentiment feedback.

Phase 1 establishes the core data ingestion and orchestration layer. An orchestrator agent, built with LangGraph, continuously monitors SCADA alarms, LIMS (Laboratory Information Management System) for water quality breaches, and weather APIs for conditions like temperature inversions that can exacerbate odor events. Upon a qualifying trigger, it immediately geofences affected residential and commercial zones using GIS data, creating the initial incident perimeter and population list for notification. This phase delivers the foundational automation that eliminates the manual, error-prone process of correlating disparate operational signals.

Phase 2 introduces multi-channel execution and human oversight gates. Based on incident severity—classified by parameters like contaminant level or geospatial impact—the workflow routes through approved communication paths. High-risk public health advisories are sent immediately via SMS and IVR using Twilio or similar APIs. Medium-risk notifications update customer portals and trigger batch emails. All actions are logged to the Customer Information System (CIS) for audit. A critical safety control is the human review gate for low-confidence or novel incidents, where a supervisor must approve the message and recipient list before dissemination, ensuring regulatory compliance.

Operational governance begins with strict trigger validation. An initial agent must confirm an incident (e.g., odor release, bypass) by cross-referencing SCADA alarms, operator logs, and sensor thresholds before any notification is authorized. This prevents false alarms. A secondary control agent then applies regulatory rules—such as mandatory reporting timelines and required message content for health advisories—ensuring every automated action is compliant with environmental and public health statutes before proceeding to geofencing and channel selection.

Rollout should be phased, starting with internal monitoring and dry-run simulations before enabling public-facing alerts. Begin with non-critical notifications, like scheduled maintenance advisories, to validate the geofencing accuracy and channel reliability. For high-severity incidents, implement a mandatory human-in-the-loop approval gate via a centralized supervisor dashboard, where incident commanders can review and modify agent-proposed messages. Post-incident, all agent decisions, message content, and delivery logs must be written immutably to a system of record (e.g., Salesforce Service Cloud, a custom audit database) to support regulatory reviews and continuous improvement of the agentic logic.