IoT-EnabledAI Solutions for Efficient Smart City Waste Management
Keywords:
Artificial intelligence, Internet of things, Smart city, Waste management, Data analytics, Predictive maintenance, Environmental sustainabilityAbstract
The rise in urbanization has resulted in considerable challenges regarding waste management in smart cities, including inefficient collection techniques, overfilled trash bins, and increasing operational expenses. Conventional waste management approaches lack the necessary intelligence and adaptability to handle the constantly changing dynamics of urban waste generation. This article outlines a comprehensive approach that leverages Artificial Intelligence (AI) and the Internet of Things (IoTs) to enhance waste management in intelligent urban environments. Merging AI-driven data analytics with IoTs-connected sensors and devices allows for real-time monitoring of waste levels and the development of predictive models for collection schedules, ultimately leading to more efficient and sustainable waste management practices. The suggested strategy employs a network of smart trash bins fitted with IoTs sensors to track elements like fill levels, weight, and temperature. The information gathered is transmitted via Low-Power Wide-Area Networks (LPWANs) to a cloud-based platform for immediate analysis. AI techniques, including machine learning models for predictive maintenance and pattern recognition, are utilized to optimize collection routes and schedules based on anticipated waste generation trends. Moreover, computer vision technologies are implemented to automate the sorting of waste and enhance recycling efforts. The introduction of the AI-driven IoTs system has considerably boosted the efficiency of waste management. Case studies indicate that the frequency of waste collection has been reduced by as much as 40%, operational costs have dropped by 30%, and recycling rates have improved by 25%. Additionally, the system has effectively minimized overflowing garbage bins, thereby enhancing public health and environmental responsibility. These findings underscore the potential of AI and IoTs technologies to transform waste management in smart cities, fostering greater adaptability, cost-effectiveness, and environmental sustainability. The method proposed serves as a foundation for future developments in smart city infrastructure and supports more sustainable urban expansion.
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