Wastewater Treatment Using Artificial Intelligence

Wastewater: A Global Picture

Wastewater is water that is unfit for use following domestic, agricultural, commercial or industrial use. The definition of wastewater also includes sources such as surface run-offs/storm water. The term is used interchangeably with “sewage”.

Far from being “useless water”, wastewater has a significant role to play in addressing the growing global demand for water. Some of these needs include energy generation, industrial development, supporting agriculture, etc.

However, the treatment of wastewater for use to meet these demands is not yet at peak levels. These facts demonstrate the situation:

i. Across the world, 80% of wastewater returns into the ecosystem untreated or unused

ii. 1.8 billion people globally use a drinking source contaminated with faeces and thus are at risk of contracting cholera, dysentery, typhoid, and polio. Nearly half (43%) of these deaths happen in children aged less than 5 years old.

One of the biggest challenges to this deficient global picture of wastewater treatment is the contamination of wastewater by pollutants and contaminants such as plant nutrients (nitrogen and phosphate), microorganisms, heavy metals (nickel, cadmium, copper), organic pollutants (polyaromatic hydrocarbons, pesticides).

The contamination of wastewater with plant nutrients especially has been linked with eutrophication – a phenomenon of excessive plant growth – which leads to oxygen depletion, reduced biodiversity, transitions in species composition and dominance, and overall decrease in water quality.

As such, wastewater can be both a blessing and a curse depending on how much proactive steps are taken to guarantee its treatment and ensure it plays a beneficial role to humanity.

Treating Wastewater with Artificial Intelligence

Most nations use either or both of centralized or decentralized systems for wastewater management. In the former case, wastewater is diverted from multiple sites of generation to central treatment centers while in the latter, wastewater is treated at the individual site or small group source.

In either case, traditional wastewater management centers usually have to deal with some of these challenges:

i. Sub-optimal state of wastewater treatment infrastructure

ii. Instability of operation systems

iii. Unreliability of information filtering into the systems

iv. Inefficient monitoring and reporting of operation system errors

v. Loss of experienced operators to retirement or death

vi. Cost of running the treatment plants

Each of these areas is a potential point of intervention for Artificial Intelligence.

For example, the falling standards of wastewater treatment infrastructure could be tackled through predictive maintenance. AI can be used to monitor sensory data about the machinery involved in wastewater treatment to make predictions about possible breakdown period. Beyond merely just notifying the technician about the anomaly, AI can also provide a specific root-cause, saving time that would otherwise have been spent troubleshooting. This functionality will help to ensure the real-time efficient monitoring and escalation of operation system errors. Intervening before the systems used to treat wastewater breakdown is an operations’ cost-saving strategy that overall promotes the longevity of the infrastructure and ensures the uninterrupted cleaning of wastewater.

The vast data gathered by AI could also be used to design more efficient methods of wastewater treatment that reduce energy consumption and promote climate saving. One water treatment plant in Germany used AI techniques to decrease energy and chemical use in its aeration process by as much as 30%.

Furthermore, AI can be used to preserve the knowledge of experienced operators and administrators in the wastewater sector by capturing and storing their wealth of experience as a database integrated into a Conversational AI agent. Such a system would function as a personal Digital AI Twin, ensuring that the information they have accrued over decades can be available for emerging generations to improve upon.

Resources:

http://www.unesco.org/new/en/natural-sciences/environment/water/wwap/wwdr/

https://www.unwater.org/publications/summary-progress-update-2021-sdg-6-water-and-sanitation-for-all/

https://www.unwater.org/app/uploads/2017/05/UN-Water_Analytical_Brief_Wastewater_Management.pdf

https://industrial-ai.skf.com/ai-for-wastewater-treatment/

https://www.xylem.com/en-us/making-waves/water-utilities-news/wastewater-treatment-plant-uses-ai-to-reduce-aeration-energy-use-by-30-percent/



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