AI-Driven Smart Waste Management: A Sustainable Approach to Urban Sustainability
Keywords:
Artificial intelligence, Geographic information system, Internet of things, Recycling, Smart cities, Smart waste management, Solid waste segregation, Sustainability, Sustainable cities, Waste-to-energyAbstract
With rapid urbanization and industrial growth, waste management has become one of the most critical environmental challenges. Traditional waste disposal methods, including manual collection and landfill dumping, are struggling to keep up with the growing volume of waste, leading to pollution, inefficient recycling, and increasing costs. Artificial intelligence (AI) is emerging as a transformative force in waste management, offering automated and data-driven solutions to enhance efficiency and sustainability. AI-driven innovations such as smart waste bins, robotic sorting systems, predictive waste models, and AI-powered waste-to-energy processes are revolutionizing the way cities manage waste. These technologies optimize collection schedules, improve recycling rates, reduce landfill dependency, and contribute to the circular economy by turning waste into valuable resources. However, challenges such as high initial costs, technological adaptation, and regulatory barriers must be addressed for widespread implementation. This paper explores AI applications in waste management, their impact on urban sustainability, and prospects for integrating AI with smart city infrastructure. By leveraging AI, cities can transition to more sustainable and cost-effective waste management systems, promoting cleaner urban environments and reducing their ecological footprint.
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