Socio-Economic-Factors Affecting Fresh Tomato Marketing in Kitgum Main Market, Uganda.

The continuous rise of urbanization has led to an overwhelming increase in waste generation with serious consequences for the environment and humans. Most waste disposal methods are inefficient, with little accountability or participation from the community, hence we propose a Smart Waste Management System (SWMS) built on AI technologies that employs computer vision and cloud computing to track on a real-time basis, facilitating improved waste sorting and the complaint making towards upcycling. The system allows the community to upload pictures of items to be reused and are identified as categories using an artificial intelligence model through which there is a trgging of the item for appropriate action. The platform also enables conversations on tracking complaints and donations of reusable items, thereby enabling data emergence for urban waste management authorities in making decisions. This paper explains the system design and implementation and is sustainability implications.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-15
DOI
https://doi.org/10.5281/zenodo.17119882
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

Socio-Economic-Factors Affecting Fresh Tomato Marketing in Kitgum Main Market, Uganda.

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Socio-Economic-Factors Affecting Fresh Tomato Marketing in Kitgum Main Market, Uganda.

article en

Abstract

The continuous rise of urbanization has led to an overwhelming increase in waste generation with serious consequences for the environment and humans. Most waste disposal methods are inefficient, with little accountability or participation from the community, hence we propose a Smart Waste Management System (SWMS) built on AI technologies that employs computer vision and cloud computing to track on a real-time basis, facilitating improved waste sorting and the complaint making towards upcycling. The system allows the community to upload pictures of items to be reused and are identified as categories using an artificial intelligence model through which there is a trgging of the item for appropriate action. The platform also enables conversations on tracking complaints and donations of reusable items, thereby enabling data emergence for urban waste management authorities in making decisions. This paper explains the system design and implementation and is sustainability implications.

Zenodo (CERN European Organization for Nuclear Research)
Bishop Stuart University (UG)
Sustainable cities and communities
Openalex Percentile: Top 43%
Geochemistry and Geologic Mapping
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