How can Big Data enable smart collection systems and protect Wastewater Treatment Plants

How can Big Data enable smart collection systems and protect Wastewater Treatment Plants

Digitization is essential for delivering centralized water collection services and supporting efficient urbanization. It allows networks to benefit from online connectivity and management platforms that feed on information (Big Data) and can handle data far more effectively than can human operators. Commonly known as Artificial Intelligence (AI) systems, these revolutionary processes have advanced the way wastewater networks can be managed, helping to protect Wastewater Treatment Plants from damage, maximizing process efficiencies and enabling expanded water reuse projects.      

big+data.pngCASE STUDY

The Greek utility EYDAP provides a prime example of how these Big Data driven systems can protect a wastewater treatment plant.

The Athens utility worked to modernize its wastewater monitoring and real-time pollution detection structure, turning to Kando’s Clear Upstream for a solution. The smart wastewater management solution initially deployed four IoT connected sensing and sampling units across EYDAP’s network; three downstream of network collectors and one close to a factory’s wastewater outlet. This deployment method enabled users to have comprehensive visibility over a large area and detect changes in wastewater quality that may indicate contamination.

During a pollution event, the IoT sampler activated autonomously, taking samples for laboratory assessment. The lab results confirmed the contamination, but Kando’s algorithm indicated the source was a different factory to that originally suspected. An IoT device was relocated, aiming to determine the source.

Following the unit’s redeployment, Kando’s engine immediately detected a polluted load and correlated it to a specific location. A particular factory was pinpointed and monitored, with further samples taken automatically during subsequent events. Sending the sample to a lab confirmed Clear Upstream’s findings. After this verification, the utility was able to make informed decisions, taking decisive action to deal with the source of the problem and reducing contamination incidents drastically.

This case study demonstrates the value of adopting AI-driven smart wastewater management tools to achieve enhanced network operations. EYDAP was able to detect abnormalities in their network, and receive insights that allowed them to make informed decisions and take preventative steps to protect wastewater treatment processes. Being able to detect, trace, track and pinpoint the source of the pollution allowed them to start a conversation with the polluter generate awareness and resulted in lowering the polluted loads in the network by 50 percent.  

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