AI-powered Strategies for Optimizing Waste Management in Smart Cities in Beijing

Abstract

The study investigates the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies into Beijing's waste management system, emphasizing their effects on operational efficiency, environmental sustainability, and economic feasibility. The deployment of AI-driven route optimization and IoT-enabled real-time monitoring resulted in a 25% reduction in waste collection trips and a 30% decrease in waste overflow incidents. These advancements led to notable reductions in fuel consumption and environmental impact, while an economic analysis projected a Net Present Value (NPV) of $3.5 million over a 10-year period, affirming the financial benefits of these technologies. The findings highlight the pivotal role of AI and IoT in optimizing urban waste management practices. The study offers policy recommendations for the phased and strategic adoption of these technologies within Beijing, with the potential to enhance efficiency and contribute to the city’s sustainability objectives. Future research is advised to examine the long-term sustainability of AI-driven waste management strategies and assess the applicability of these technologies in diverse urban environments.