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ZENODO
Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN MUNICIPAL SOLID WASTE MANAGEMENT AT ITAM, UYO

Authors: Oparaji, Uzochukwu N.;

OPPORTUNITIES FOR ARTIFICIAL INTELLIGENCE IN MUNICIPAL SOLID WASTE MANAGEMENT AT ITAM, UYO

Abstract

This study aimed to identify the challenges of municipal solid waste management in Itam, Uyo and to proffersolutions to addressing them. The study identified inadequate public waste disposal bins in the area study evenas the populace refered dumping their waste in public disposal units for it to be collected the responsible wastemanagement agency. The ineffective collection of waste at collection points occasioned indiscriminate dumpingof waste. To addressing these challenges, this paper presented a strategy of improving waste managementprocess by utilizing Artificial Intelligent ‘AI’ to optimizing waste collection routing of garbage trucks forefficient tracking and monitoring of waste management facilities, estimating the waste generation patterns at thewaste collection points and for efficient planning and allocation of MSW management resources. IncorporatingAI in the municipal solid waste management system enhances its operational guidelines and efficiency.

Keywords

Artificial Intelligent, Municipal solid waste

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green