Published
2025-06-30
Section
Articles
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Smart Waste Management: Leveraging IoT and Data Analytics for Sustainable Cities in Pakistan
Muhammad Irfan
Department of Urban and Regional Planning, University of Engineering and Technology, Lahore, Pakistan
Salman Raza
Department of Computer Science, Lahore University of Management Sciences, Lahore, Pakistan
Keywords: Smart Waste Management, IoT, Data Analytics, Sustainable Cities, Pakistan, Urban Waste, Sensor Networks, Predictive Modeling
Abstract
Rapid urbanization and population growth in Pakistan have significantly increased solid waste generation, leading to environmental degradation, public health risks, and inefficient municipal waste management. Traditional waste management systems are often reactive, lacking real-time monitoring and predictive capabilities. This study explores the integration of Internet of Things (IoT) technologies and data analytics to optimize waste collection, resource allocation, and environmental sustainability in urban Pakistan. By analyzing IoT-enabled smart bins, sensor networks, and predictive data models, this research demonstrates the potential for reducing operational costs, improving waste segregation, and enhancing citizen engagement. The findings underscore the need for a policy-driven approach to implement smart waste solutions, emphasizing sustainable urban development.
References
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