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DOI: 10.14569/IJACSA.2025.0160471
PDF

Towards an Optimization Model for Household Waste Bins Location Management

Author 1: Moulay Lakbir Tahiri Alaoui
Author 2: Meryam Belhiah
Author 3: Soumia Ziti

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 4, 2025.

  • Abstract and Keywords
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Abstract: Smart cities require effective, adaptive household waste management systems due to rapid urbanization. Traditional bin placement strategies based on placing bins equidistant among residents fail to account for actual human behavior, leading to overflowing or underused bins. This paper addresses optimizing bin location and capacity through Internet of things (IoT) technologies and data-driven decision-making by deploying LoRaWAN sensors in Tangier City as a case study; real-time usage information was then collected and analyzed. Through statistical analysis and outlier detection techniques, the proposed approach identifies bin placements that are non-optimized by using statistical analysis. It also evaluates data quality and classes bins by their usage level; results show several bins were constantly overused or underused indicating that dynamic placement and capacity adjustment would improve waste collection efficiency, reduce operational costs and enhance citizen satisfaction within a Smart City framework.

Keywords: Smart City; IoT; household waste; LoRaWan; bin location; outlier detection

Moulay Lakbir Tahiri Alaoui, Meryam Belhiah and Soumia Ziti, “Towards an Optimization Model for Household Waste Bins Location Management” International Journal of Advanced Computer Science and Applications(IJACSA), 16(4), 2025. http://dx.doi.org/10.14569/IJACSA.2025.0160471

@article{Alaoui2025,
title = {Towards an Optimization Model for Household Waste Bins Location Management},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160471},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160471},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {4},
author = {Moulay Lakbir Tahiri Alaoui and Meryam Belhiah and Soumia Ziti}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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