Using IoT to monitor pumps and undertake predictive and preventative maintenance.

Remote monitoring of wastewater pump stations enabling predictive and preventative maintenance

The solution

The solution was designed to collect real-time data using new flowmeters and power meters added to existing machinery in order to provide continuous performance metrics and maintenance insights. As pumps types vary, the solution needed to flexibly accommodate a range of equipment types in operation.

Defining what data to collect is critical
In order to create this solution, we identified the key metrics required to achieve the desired business objectives. In this solution, this included:

1. Waste pit levels
2. Flowrate and totalized flows 
3. Pressure on the inlet and outlet of the pump
4. Pump power consumption
5. Pump energy efficiency

Initial goals of the solution
Working with our partners, we installed flow meters and energy meters before connecting them via Modbus to a 4G gateway,  so that we could then:

1.  Monitor critical operational data received from the equipment via a web-based system
2.  Ensure device management monitoring was set in place
3.  Define business logic for the application in-order to meet the business objectives
4.  Provide alarm and alert notifications via email or SMS messages
5.  Start collecting historical data to undertake pump efficiency modelling
6.  Provide the right dashboards to the right users with the right insights
7.  Test the application, making sure all of the above goals are met, based on the solution architecture

Before go-live, we tested four critical aspects of the solution:

Security
The Rayven IoT platform is built with security as a top priority and our proprietary security architecture ensures that data is secure at all points of the IoT environment.

The solution includes data encryption in transit from device-to-cloud, as well as device authentication; security (Bearer) tokens; SSL, AES and RSA encryption; as well as additional device security checks done via automated polling.

Connectivity
None of the existing equipment was automated, and so a critical step in this solution was to add the right sensors, create local Modbus connectivity and install a 4G gateway to ensure a reliable, continuous real-time connection.

Data integrity
Your ability to make the right decisions is entirely reliant on the integrity of the data you collect, therefore, making sure that any  solution has reliable connectivity is key to ensuring your data is always up-to-date and that you can rely on it to make critical business decisions in real-time. However, things do go wrong, so with this solution, it was critical for us to test that the data coming from the water facility matched that being shown on the dashboards and to build in capability to back-fill data in sequence in the event that any communication link ever went down, such as through a 4G outage.

Industrial data science
The objectives of the exploratory data analysis was to monitor pump-house performance and efficiency, which included:

1.  Calculating flow rate by minute, hour, day, and week
2.  Forecasting daily water flow
3.  Understanding pump utilization
4.  See pump energy efficiency (both whilst pumping and when idle)
5.  Leak detection with minimal false positives

What’s next?

We are continuing to add additional pumps to the solution and improve our maintenance forecasting results. In addition, we are planning to add real-time energy pricing to provide a more precise view of costs, as prices are dynamic during the day.