Across the water and wastewater industry, utilities are under increasing pressure to modernize aging infrastructure while maintaining safe, reliable, and compliant operations. A regional municipal water utility operating treatment plants, pumping stations, and wastewater facilities across several counties needed a scalable way to bring AI-powered monitoring closer to critical infrastructure. Premio helped the utility deploy Premio’s compact fanless AI edge computer with remote management capabilities to support real-time video analytics, facility safety, and infrastructure visibility.
Challenges
- Existing systems lacked sufficient AI processing performance for real-time video analytics
- Limited onsite IT resources made multi-facility edge deployment difficult to manage
- Continuous operation of monitoring systems was critical for utility infrastructure
- Wall mounted installations required a compact industrial platform for existing control cabinets
- Diagnosing and recovering unresponsive systems often required costly site visits
Solutions
- Premio’s entry-level AI edge computer powered by NVIDIA Jetson Orin Nano and NX modules (JCO-1000-ORN-A)
- Premio’s EDGEBoost OOB for centralized visibility and management across multiple facilities
- Up to 157 TOPS AI processing for real-time video analytics and infrastructure monitoring
- Hardware level remote recovery and power control to minimize onsite maintenance visits
- Compact fanless design for reliable wall mounted deployment inside facility control cabinets
Benefits
- Real-time AI monitoring across utility sites
- Reduced onsite maintenance visits
- Reliable deployment in compact control spaces
Company Overview
A regional municipal water utility provides essential water treatment, pumping, and wastewater services across several counties in the United States. The organization excels at maintaining dependable public infrastructure while meeting strict safety, operational, and regulatory expectations. As utility operations become more connected and data driven, the organization is investing in AI-powered edge monitoring to improve resilience, visibility, and long-term service reliability.
The Challenges
Limited AI Processing at the Edge
Existing monitoring systems were not designed to handle real-time video analytics across distributed utility sites. As the utility expanded its use of AI for leak detection, equipment monitoring, PPE compliance, intrusion detection, and visual inspection, traditional computing infrastructure could not provide the needed performance at the edge. The organization needed an industrial AI platform capable of processing video streams locally without relying on centralized cloud resources.
Multi-Site Deployment with Limited IT Resources
The utility operated across multiple treatment plants, pumping stations, and wastewater facilities, many with limited onsite IT support. Managing edge computers at each location created a challenge because routine troubleshooting could require staff to travel between sites. A more centralized approach was needed to help teams monitor system health, manage uptime, and respond quickly when devices required attention.
Continuous Monitoring for Critical Infrastructure
Water and wastewater facilities depend on continuous visibility to maintain safe and reliable operations. Any interruption to AI monitoring could reduce awareness around pumps, valves, restricted areas, and other critical infrastructure. The edge computing platform needed to support dependable operation in environments where downtime could affect safety, compliance, and service continuity.
Compact Wall Mounted Installation Requirements
Many of the utility’s facilities already had established control cabinets and limited available space for new technology. The selected computer needed to fit into existing infrastructure without requiring major cabinet redesigns or complex installation changes. A compact industrial form factor was essential for wall mounted deployment near facility equipment and monitoring systems.
Costly Site Visits for System Recovery
When systems became unresponsive, diagnosing or recovering them often required an onsite maintenance visit. For a utility spread across multiple counties, these visits increased cost, response time, and operational burden. The organization needed a way to remotely recover and power cycle edge systems at the hardware level to reduce unnecessary field support.
The Solution
Premio’s entry-level AI edge computer powered by NVIDIA Jetson Orin Nano and NX modules (JCO-1000-ORN-A)
Centralized Remote Management and Hardware Level Recovery with EDGEBoost OOB
Premio’s EDGEBoost OOB provided centralized visibility and management for edge deployments across multiple facilities. Operations and IT teams could monitor device status, manage distributed systems, and respond to issues remotely, which was especially valuable for sites with limited onsite IT resources.
Because the system integrated Premio’s EDGEBoost OOB technology, the utility gained hardware level remote recovery and power control for unresponsive edge devices. Instead of immediately dispatching technicians to remote treatment plants or pumping stations, teams could perform recovery actions remotely to restore system operation more efficiently. This helped reduce costly site visits while maintaining continuous monitoring for safety, reliaility, and regulatory compliance.
Industrial AI Edge Computing for Real-Time Video Analytics
The utility selected the JCO-1000-ORN-A to bring AI processing directly into water treatment plants, pumping stations, and wastewater facilities. Powered by NVIDIA Jetson Orin Nano and NX modules, the system delivered up to 157 TOPS of AI performance for real-time video analytics at the edge. This enabled local AI models to support leak detection, equipment status monitoring, PPE compliance, restricted area intrusion detection, and remote visual inspection of critical infrastructure.
By processing video analytics locally, the utility gained faster insights while reducing dependence on centralized servers and network bandwidth. The compact fanless design also made the system suitable for deployment inside existing control cabinets across distributed utility sites.
Compact Fanless Cabinet Deployment
The compact fanless design made the JCO-1000-ORN-A well suited for wall mounted installation inside existing control cabinets. Its rugged industrial design supported reliable operation near pumps, valves, controls, and monitoring equipment commonly found in utility environments. By fitting into existing facility infrastructure, the platform simplified deployment without requiring major changes to the customer’s cabinet layouts.
The Benefits
Real-Time Infrastructure Visibility
The utility gained local AI processing for faster detection of leaks, equipment status changes, safety events, and restricted area activity across distributed facilities.
Lower Maintenance Burden
EDGEBoost OOB enabled remote visibility, power control, and recovery, helping reduce costly onsite visits and improving support responsiveness from Premio’s Los Angeles team.
Reliable Fit for Utility Environments
The compact fanless design allowed the system to be wall mounted inside control cabinets while supporting dependable operation in water and wastewater facilities.
Conclusion
By deploying the JCO-1000-ORN-A with EDGEBoost OOB, the municipal water utility strengthened its ability to monitor critical infrastructure across multiple facilities. The solution brought real-time AI analytics, remote management, and rugged edge reliability into existing utility environments. As the organization continues modernizing operations, industrial AI edge computing provides a scalable foundation for safer, more resilient, and more compliant water infrastructure.
To learn more about the JCO-1000-ORN-A series and our remote management solutions, contact Premio’s experts at sales@premioinc.com.