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water-4

Water

Organizations managing water systems face common challenges, like inefficient and outdated equipment, complex SCADA systems, and a limited number of experienced technicians. Exosite’s ExoSense® condition monitoring application can quickly enhance existing water systems with cloud-based remote monitoring that increases efficiencies, optimizes personnel resources, reduces costs, and mitigates potential downtime.

Real-Time Dashboards

Remotely monitor real-time and historical data—like pH, flow, turbidity, and tank levels—through customizable, HMI-like dashboards from any computer, tablet, or smartphone.

Condition-Based Alerting

Receive email and SMS alerts based on configurable rules—like sustained thresholds or variances—that are intuitive to set up and modify.

Legacy Equipment

Easily connect to existing SCADA systems, PLCs, and controls or add connected sensors to older equipment to enhance capabilities and gain new insights.

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Eliminate Unnecessary Downtime and Water Quality Issues

ExoSense provides real-time insights, condition-based alerts, and historical trends that technicians can configure using their in-depth knowledge of unique water systems. Support personnel can then better anticipate issues, maintain inventory of critical parts and chemicals, and perform maintenance before downtime occurs. 

Do More With Fewer People

ExoSense allows multiple pieces of equipment, systems, and facilities to be monitored from one simple application. As a result, technicians can support a larger number of municipalities remotely, so they can do more, travel less, and lower operational costs. As an added benefit, cloud-based monitoring solutions are significantly simpler and lower cost than SCADA-based systems.

Pump-Based Anomaly Detection

Sensors can be fitted to industrial pumps to monitor a number of data sources, like RPMs, device and ambient temperature, electrical current, humidity, and vibration. This data can then be aggregated and incorporated into advanced algorithms that detect performance anomalies, predict machine failure, and enable preventative maintenance to reduce costly downtime.

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Challenges:

  • Need data analysis over a significant amount of time from a large number of pumps
  • Require implementation of analytic algorithms in a connected solution
  • Need to be able to make adjustments to their solution in real time
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