The Impact of IoT-Enabled Routing Optimization on Waste Collection Distance: A Systematic Review and Meta-Analysis

Rafael R. Maciel (), Adler Diniz de Souza, Rodrigo M. A. Almeida and João Paulo R. R. Leite
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Rafael R. Maciel: Institute of Systems Engineering and Information Technology, Federal University of Itajubá (UNIFEI), Itajubá 37500-903, MG, Brazil
Adler Diniz de Souza: Institute of Mathematics and Computing, Federal University of Itajubá (UNIFEI), Itajubá 37500-903, MG, Brazil
Rodrigo M. A. Almeida: Institute of Systems Engineering and Information Technology, Federal University of Itajubá (UNIFEI), Itajubá 37500-903, MG, Brazil
João Paulo R. R. Leite: Institute of Systems Engineering and Information Technology, Federal University of Itajubá (UNIFEI), Itajubá 37500-903, MG, Brazil

Logistics, 2025, vol. 9, issue 4, 1-27

Abstract: Background : Waste collection is a critical logistical challenge in urban management, and while Internet of Things (IoT) technologies are increasingly used to optimize collection routes, a systematic, quantitative synthesis of their impact is lacking. This study aims to bridge this gap by quantifying the effect of IoT-enabled routing optimization on waste collection distances. Methods : We conducted a systematic review and meta-analysis following the PRISMA protocol, searching the Scopus, IEEE Xplore, and ACM Digital Library databases. This process yielded 11 eligible studies, providing 21 distinct samples for quantitative synthesis. Results : The analysis reveals that IoT-enabled routing optimization reduces collection distance by a combined average of 21.51%. A significant disparity was found between study types, with simulation-based approaches reporting higher reductions (−39.79%) compared to real-world deployments (−12.37%). No statistically significant performance differences were observed across different routing algorithm categories or Vehicle Routing Problem (VRP) variants. Conclusions : These findings provide robust quantitative evidence of the significant efficiency gains from implementing IoT-based smart waste management systems. The gap between simulated and real-world results underscores the need for practitioners to set realistic expectations, while our analysis supports the adoption of these technologies for more sustainable urban logistics.

Keywords: internet of things; smart waste management; vehicle routing problem; route optimization; meta-analysis (search for similar items in EconPapers)
JEL-codes: L8 L80 L81 L86 L87 L9 L90 L91 L92 L93 L98 L99 M1 M10 M11 M16 M19 R4 R40 R41 R49 (search for similar items in EconPapers)
Date: 2025
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