Artificial Intelligence in Water Industry

The water sector is embracing artificial intelligence (AI), which powers machine learning-based intelligent operations that maximize resource consumption and operational budgets for businesses. Here are 10 ways artificial intelligence is already altering the water sector.

Operations related to water and wastewater are investing in AI (AI). By 2030, AI solutions are expected to receive investments of $6.3 billion, according to market research. This investment is a part of a larger movement within the water sector to adopt smart infrastructure solutions and 'get digital.'

The potential for savings is enormous when some US utilities spend more than $300 year on water and wastewater operations per user. By lowering energy costs, maximizing the use of chemicals for treatment, and enabling proactive asset maintenance, AI can reduce operating expenditures by 20–30%.

For utilities, water main breaks are expensive in terms of both financial and social capital. In order to make alerts increasingly accurate over time, AI and machine learning can 'fingerprint' the data patterns that suggest a break event may be about to occur.

Operators are no longer required to independently examine complex factors for crucial decisions. AI allows 'Operator 2.0' with intelligent recommendations and machine learning-driven decision-making, whether it's controlling the operation of pumps, calculating chemical dosages, or selecting whether to maintain assets.

The EPA states that drinking water and wastewater treatment facilities are many municipal governments' biggest energy consumers, frequently making up 30 to 40% of total energy used. Actually, the United States uses about 2% of its energy for drinking water and wastewater infrastructure. Pump runtimes can be optimized using AI so that energy is only consumed when it is necessary. For those who use AI early on, this might be a simple cost-reduction victory.

Numerous governmental and commercial businesses are required to comply with effluent compliance regulations. To ensure that effluence criteria are followed and that compliance fines are avoided, AI learns from the distinctive features of your site.

Data management has become more difficult as a result of the increase in data that is now accessible to managers of water operations. Social media, CMMS, and SCADA systems all contain a lot of information that can be used to enhance operations. With the help of AI, this heterogeneous data can be cleaned, made relevant, secure, and used to generate suggestions with high accuracy.

How can you guarantee that an experienced operator's priceless expertise is kept when they leave the workforce? AI-powered dashboards will maintain uniform documentation of institutional knowledge.

Reactive asset maintenance is quickly being abandoned by early users of AI. Although time-based maintenance is simple to administer, it causes unneeded uptime and deterioration. Let AI inform your team of the assets that require maintenance and when.

Organizations can seek data-driven, intelligent management of water systems as a result of the deployment of AI. As a result, water management will be dependable, long-lasting, and affordable.