Data science applied to solid waste management in Los Ríos-Ecuador
DOI:
https://doi.org/10.29076/issn.2528-7737vol18iss49.2025pp01-11pKeywords:
sustainable management, non-hazardous waste, segmentation, data mining, machine learningAbstract
Solid waste management is a challenge for cities and countries due to urbanization and population growth. This fact creates the need to explore options that facilitate analysis, such as Data Science. Therefore, this study applied techniques like Clustering to analyze the generation and management of non-hazardous solid waste, using the cantons of the Los Ríos province in Ecuador as a case study. Sixteen influential variables were identified through Chi-Square and ANOVA analysis, and Clustering algorithms (K-Means, DBSCAN, and Hierarchical Clustering) were applied to group cantons with similar characteristics. The results show that most cantons do not properly classify waste and dispose of it along with household waste. However, some cantons implement efficient practices such as composting and recycling. Therefore, the implementation of educational programs and specific strategies for each group of cantons is recommended, based on the identified patterns
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