Artificial intelligence in solid waste management in India: current status and future prospects.

Area of Science:

• Environmental Science
• Computer Science
• Engineering

Background:

• Rapid economic growth in India has led to increased energy consumption and solid waste generation, causing significant environmental and health issues.
• Effective solid waste management (SWM) is crucial for mitigating these adverse effects and promoting sustainable development.

Purpose of the Study:

• To investigate the integration and impact of artificial intelligence (AI) in India's solid waste management (SWM) sector.
• To assess AI's potential for improving operational efficiency, reducing costs, and minimizing environmental consequences in SWM.

Main Methods:

• Review of recent AI technologies applied to waste segregation, route optimization, resource recovery, and recycling.
• Analysis of machine learning, computer vision, and predictive analytics in SWM.
• Examination of case studies from Indian cities implementing AI-based waste management solutions.
• Critical discussion on the application of Life Cycle Assessment (LCA) for evaluating AI-based SWM systems' sustainability and financial viability.

Main Results:

• AI technologies demonstrate significant potential in enhancing waste segregation, optimizing collection routes, and improving recycling rates.
• Case studies illustrate successful implementation of AI in Indian cities, leading to more efficient waste management.
• Life Cycle Assessment (LCA) provides a framework for evaluating the environmental and economic benefits of AI in SWM.

Conclusions:

• AI offers a transformative potential for restructuring India's SWM strategies, paving the way for more sustainable and efficient waste handling.
• The adoption of AI in SWM is essential for addressing the challenges posed by increasing waste generation and ensuring environmental protection.