Real-time Telematics with IoT Gateways

In this case study, we’ll uncover how a global leader in municipal and industrial wastewater treatment to gain operational transparency and predictive analytics for their facilities utilizing industrial IoT gateways.

The Challenge

The wastewater treatment organization needed to replace their existing IoT gateway solution as it failed to meet the required wide operating temperature ranges, compromising performance and reliability. The solution needed to meet a checklist of deployment requirements: fitted into a compact NEMA enclosure, DIN-rail mounted, and operate reliably in extreme temperatures.

The Solution

After reaching out to Premio, they suggested the RCO-1000-EHL Series due to its ultra-compact form factor, world-class certifications, rich IoT connectivity, and low-power efficiency.

Real-Time Predictive Analytics for Water Treatment Plant Operations

The RCO-1000-EHL is deployed on-premises to ensure 24/7 operations for real-time data aggregation and storage. Edge computing enables real-time insights and allows water treatment plant operators to remotely monitor for actionable decision-making, as well as establish predictive analytics for significant improvements in operational efficiency.

IoT-Centric Connectivity for Homogenous Data Flow

Pumps, pressure gauges, water meters, and so on are all various IoT sensors that provide data to the RCO-1000-EHL. The industrial mini computer consolidates these IoT sensors for seamless monitoring and communication with a homogenous data flow.

Rugged Reliability with Fanless & Cableless Design

The RCO-1000-EHL is purpose-built with a fanless and cableless design to withstand extreme temperatures and harsh environments for long-term, maintenance-free durability.

Why Premio?

With 35+ years of rugged edge manufacturing expertise, Premio provides not only the ideal hardware, but also exceptional OEM flexibility and support. Their turnkey support team and robust supply chain capabilities ensured rapid deployment and minimized lead times.