Status and future trends in wastewater management strategies using artificial intelligence and machine learning...

Area of Science:

• Environmental Science
• Water Resource Management
• Computer Science

Background:

• Global water crisis necessitates innovative solutions for water collection and recycling.
• Effective water management requires intelligent mechanisms considering population density and diverse usage needs.

Purpose of the Study:

• To review the latest trends in water and wastewater recycling.
• To explore the application of Artificial Intelligence (AI), machine learning (ML), Deep Learning (DL), and the Internet of Things (IoT) in water management.

Main Methods:

• Review of existing literature on water management strategies.
• Investigation of AI, DL, and IoT applications in water distribution, rainfall collection, and irrigation control.
• Analysis of case studies and statistical data for framework development.

Main Results:

• AI, ML, DL, and IoT offer promising solutions for efficient water distribution and conservation.
• Data from various sources can be integrated into intelligent water management systems.
• Intelligent systems can help meet water quality requirements for diverse applications.

Conclusions:

• An integrated framework using AI, DL, and IoT can enhance water management efficiency.
• Intelligent water management is crucial for addressing the global water crisis.
• Further research and implementation of these technologies are recommended.