AI-Driven Water Consumption Optimization

Client

Wideverse srl

Market

Italy

Industry

Water Supply and Management

Challenge

Accurate predictions of water flow and consumption can optimize resource management and reduce operational costs but they are difficult.

How Dynius helped

Dynius developed an AI-based prediction algorithm using graph neural networks to enhance water distribution efficiency.

The solution

Dynius collaborated with an important water distributor in southern Italy to implement a state-of-the-art AI-driven prediction algorithm tailored for water consumption and flow management. Leveraging graph neural networks, the solution can accurately forecast water usage across various nodes in the distribution network, considering different configurations. This technology integrates seamlessly with the client's existing systems, ensuring smooth deployment and operation.

Key features include:

• Graph neural networks provide good estimations for water flow and consumption under various conditions.
• The algorithm can handle different network configurations, making it robust and versatile.
• The solution can easily be integrated with existing water network infrastructures.

Reduced Energy Consumption

Optimized water distribution reduces the energy needed for pumping and treatment.

Cost Savings

Enhanced resource management leads to significant reductions in operational expenses.

Enhanced Resource Allocation

Precise forecasts ensure efficient water allocation, preventing both shortages and oversupply.

Improved Sustainability

Lower energy use and minimized resource waste contribute to environmental sustainability.

Takeaways

Dynius’s AI-driven solution provided significant efficiency gains, cost reductions, and enhanced sustainability. This collaboration demonstrates the transformative potential of AI in resource management within the water supply industry.