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Trimble > Case Studies > IoT Implementation in San Francisco Public Utilities Commission: A Case Study
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IoT Implementation in San Francisco Public Utilities Commission: A Case Study

 IoT Implementation in San Francisco Public Utilities Commission: A Case Study - IoT ONE Case Study
Technology Category
  • Cybersecurity & Privacy - Intrusion Detection
  • Sensors - Liquid Detection Sensors
Applicable Industries
  • Electrical Grids
  • Utilities
Applicable Functions
  • Maintenance
  • Quality Assurance
Use Cases
  • Leakage & Flood Monitoring
  • Water Utility Management
Services
  • System Integration
  • Testing & Certification
The Challenge
The San Francisco Public Utilities Commission (SFPUC), the third largest municipal utility in California, provides water, wastewater, and electric power services. The SFPUC manages an extensive wastewater system that collects, conveys, and provides secondary treatment to combined sewage flows within the City and County of San Francisco. However, like many utilities, SFPUC faces challenges such as environmental compliance, climate variability, aging infrastructure networks, financial shortages, and labor efficiencies. The SFPUC's environmental monitoring program is driven by regulatory compliance, calibration of the city-wide hydraulic and hydrologic (H&H) model, establishment of repair and rehabilitation prioritization, and real-time operational decision support. Other factors include early warning from collection system to plant operations, pre-development monitoring for upgrades, and forensic analysis of wet-weather and storm effects.
The Customer

San Francisco Public Utilities Commission (SFPUC)

About The Customer
The San Francisco Public Utilities Commission (SFPUC) is the third largest municipal utility in California, providing essential utility services such as water, wastewater, and electric power. The SFPUC manages a vast wastewater system that collects, conveys, and provides secondary treatment to combined sewage flows within the City and County of San Francisco. The system includes 1,010 miles of sewer pipes, a wet weather transport/storage system, and three treatment plants taking in flows from roof drains, domestic sewage, and street runoff. The SFPUC's mission is to provide high quality, efficient, and reliable services in a manner that is inclusive of environmental and community interests, and that sustains the resources entrusted to its care.
The Solution
To address these challenges, SFPUC implemented Trimble's Telog family of Internet of Things (IoT) wireless battery-powered data recorders. These devices enable utilities to collect, monitor, and manage water and environmental data collected from the field, and access the information via the web and mobile applications. Trimble Telog Enterprise software securely captures and centrally stores remote monitoring data, processes alarms and alerts, and allows data access for third-party software. Its alarm-based messaging activates when rain or flow has exceeded a critical threshold, assisting in the decision-making process and tracking correlation between multiple data sets or trends in real time. The SFPUC uses Trimble wireless monitoring technology for its speed of deployment, open architecture, rapid scalability, and minimal engineering. The solution also provided a lower total cost of ownership compared to traditional SCADA technologies.
Operational Impact
  • Since implementing Trimble’s system, the SFPUC has experienced several operational benefits. The system has enabled the SFPUC to use data to support operational decision-making in real-time, prioritize repairs and rehabilitation, and develop calibrated models. It has also increased the SFPUC's knowledge of the system and ability to do forensic analysis, such as pipe flow reversal during wet weather. The SFPUC management decided subsequent actions would incorporate real-time web API for the public where appropriate, a low-power radio mesh network such as LTE-M or LoRaWAN, and RTDs to integrate real-time data and rain forecast with a simplified H&H model. The system was able to adapt well and it provides near real-time data in critical locations.

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