Artificial intelligence for waste management in smart cities: a review

Area of Science:

• Environmental Science
• Computer Science
• Engineering

Background:

• Global waste generation presents significant pollution and management challenges.
• Innovative strategies are needed to improve the waste ecosystem.
• Artificial intelligence (AI) is emerging as a transformative technology in waste management.

Purpose of the Study:

• To review the diverse applications of AI in the waste management sector.
• To highlight AI's potential in optimizing waste logistics, sorting, and energy recovery.
• To explore AI's role in creating efficient and cost-effective waste management systems for smart cities.

Main Methods:

• Comprehensive literature review of AI applications in waste management.
• Analysis of AI's impact on key performance indicators like transportation distance, cost, and time savings.
• Examination of AI's accuracy in waste identification and sorting.
• Assessment of AI's integration with chemical analysis for waste pyrolysis and energy conversion.

Main Results:

• AI in waste logistics can reduce transportation distance by up to 36.8%, costs by 13.35%, and time by 28.22%.
• AI achieves high accuracy (72.8% to 99.95%) in identifying and sorting waste materials.
• AI integration enhances waste pyrolysis, carbon emission estimation, and energy conversion efficiency.
• AI adoption leads to increased process efficiency and cost reductions in smart city waste management.

Conclusions:

• AI presents a powerful toolkit for addressing global waste management issues.
• AI significantly optimizes waste logistics, sorting accuracy, and resource recovery processes.
• Implementing AI in waste management systems is crucial for enhancing efficiency, reducing costs, and improving public health in smart cities.