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CS-2032: AI-Enabled Mobile Framework for Sustainable E-Waste Management in Developing Countries
Author(s):
1. Sabeeh Fatima: Department of Computer Science, Namal University Mianwali,,Pakistan
Abstract:
Electronic waste (e-waste) has become an inevitable outcome of technologicalgrowth. In developing regions, its informal handling without regulation or safetymeasures is escalating environmental and public health risks. Although currentAI research in e-waste management focuses on automated sorting, recycling,and IoT systems for smart cities, the application of AI frameworks inunderserved communities remains unexplored. Moreover, researchers aredesigning AI-based solutions, but they are often challenging to implement inresource-constrained settings, such as rural areas and small towns. This researchstudy presents a mobile and AI-enabled e- waste management frameworkdesigned for developing countries to monitor e-waste flows across thehousehold-to-recycler value chain. It emphasizes the collaboration between localgovernments, scrap collectors, and formal recyclers to enable the development ofa digitally traceable and sustainable e-waste ecosystem. This proposed approachaims to reduce illegal dumping and hazardous recycling practices and bringtransparency in e-waste flows. It provides governments and industries with datadriveninsights to effectively design recycling policies. By combining mobileplatforms with AI-driven traceability, the study introduces an innovative modelfor e-waste governance that can be replicated globally.
Page(s): 108-108
DOI: DOI not available
Published: Journal: 4th International Conference of Sciences “Revamped Scientific Outlook of 21st Century, 2025” , November 12,2025, Volume: 1, Issue: 1, Year: 2025
Keywords:
traceability , sustainable computing , mobile platforms , AI for sustainability , Ewaste management
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