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

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.

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Publication Details

Journal
Journal of improved oil and gas recovery technology.
Published
2024-09-12
DOI
https://doi.org/10.53469/wjimt.2024.07(05).02
Citations
9
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
2.88
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article

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

Junhao Weng, Yao Yao, Chao He, Peng Xiao et al.
9 citations
Journal of improved oil and gas recovery technology.
Smart Cities and Technologies
2.88
article

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

Junhao Weng, Yao Yao, Chao He, Peng Xiao, C. Hong Gong
article en
9 citations

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.

Journal of improved oil and gas recovery technology.Vol. 7(5)
Amazon (United States) (US), DHC Software (China) (CN), Yonyou (China) (CN)
Openalex Percentile: Top 8%
Smart Cities and Technologies
2.88
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AI-powered Strategies for Optimizing Waste Management in Smart Cities in Beijing — Junhao Weng, Yao Yao, et al. · Journal of improved oil and gas recovery technology. (2024) | TGRS Research Map | TGRS