Blog

In the wake of COVID-19, people have become more aware of germs and viruses lurking on their phone screens, door handles, and other surfaces. As a consequence, various wipes and paper towels have become exceedingly popular, resulting in an increase in sewer blockages. Unlike toilet paper, these products do not break apart in the sewers but instead form solid blockages that water utilities then have to deal with. While the first priority in addressing this problem is prevention through education, the second is for water utilities to find suitable tools to detect blockages in their network and, if possible, to do so while working remotely.

A blockage that goes undetected for too long results in a sewer overflow. In practice, an overflow means there is wastewater somewhere it should not be: in rivers, lakes, at beaches, in a basement or garage. A single blockage can cause environmental and material damage, not to mention heartache in case of a flooded property. Wastewater is full of contaminants that needs to flow into a water treatment plant, not linger in our living environment.

Combining multiple data sources produces new information

Digitalization and sewer blockages have not always belonged in the same sentence. But in the wave of digitalization in all sectors, new opportunities for water utilities as well. Collecting data is not new to the water industry: there are meters in place to measure the flow of water and pump usage, among other things. The opportunity, however, lies in taking advantage of all of the data combined. Comparing real-time measurements with historical data is informative, but even more value can be added by combining it with other data sources such as weather conditions or sea levels.

So, how do we harness the data in a useful way? Simply having it does not tell a water utility very much. Blockage risks can be managed by applying intelligent analysis to large amounts of data. Neuroflux’s approach is to use artificial intelligence (AI) to form models of past data that are then automatically compared with real-time measurements. The AI system uses data from multiple sources such as weather radars, utilities’ control systems and GIS platforms, making the detection process even more reliable. Once an anomaly is detected, AI generates an alert, giving the water utility crew an opportunity to react quickly.

At Neuroflux, we have always developed our tool in consultation with experts in the water industry, and blockages were the very first thing we started detecting with data analysis. In our experience, the best solutions are discovered when you combine expertise from different fields. If blockages are an issue in your area, we’d be happy to discuss what your data can do for you.