Version 1
: Received: 26 September 2024 / Approved: 27 September 2024 / Online: 27 September 2024 (12:31:16 CEST)
How to cite:
Gallegos, L. F. J.; Gamarra Tuco, R.; Espinoza Vigil, A. J. Smart Road Maintenance: Using Smart Technologies for Maintenance Management on Local Roads. Preprints2024, 2024092175. https://doi.org/10.20944/preprints202409.2175.v1
Gallegos, L. F. J.; Gamarra Tuco, R.; Espinoza Vigil, A. J. Smart Road Maintenance: Using Smart Technologies for Maintenance Management on Local Roads. Preprints 2024, 2024092175. https://doi.org/10.20944/preprints202409.2175.v1
Gallegos, L. F. J.; Gamarra Tuco, R.; Espinoza Vigil, A. J. Smart Road Maintenance: Using Smart Technologies for Maintenance Management on Local Roads. Preprints2024, 2024092175. https://doi.org/10.20944/preprints202409.2175.v1
APA Style
Gallegos, L. F. J., Gamarra Tuco, R., & Espinoza Vigil, A. J. (2024). Smart Road Maintenance: Using Smart Technologies for Maintenance Management on Local Roads. Preprints. https://doi.org/10.20944/preprints202409.2175.v1
Chicago/Turabian Style
Gallegos, L. F. J., Rubén Gamarra Tuco and Alain Jorge Espinoza Vigil. 2024 "Smart Road Maintenance: Using Smart Technologies for Maintenance Management on Local Roads" Preprints. https://doi.org/10.20944/preprints202409.2175.v1
Abstract
This research seeks to provide local governments with a comprehensive alternative for the proper maintenance of roads, focusing on the surface and functional evaluation of pavements. It com-pares conventional methods of the International Roughness Index (IRI) and the Pavement Condi-tion Index (PCI) with novel methodologies that employ smart technologies. Road maintenance is essential for economic development, facilitating the circulation of services and resources. This re-search analyzes the efficiency of smart technologies in the maintenance of local roads in Arequipa, taking as a case study a 2 km section of the AR-780 highway in Polobaya. The International Roughness Indices (IRI) obtained through the Merlin Roughness Meter and the Roadroid applica-tion were compared, finding a minimum variation of 4.007% in the left lane and 8.5% in the right lane. Roadroid turned out to be 60 times faster than the conventional method, with a cost differ-ence of 220.11 soles. Both methods classified the road condition (PSI) as GOOD, validating the accuracy of Roadroid. In addition, the Pavement Condition Index (PCI) was evaluated with con-ventional methods and a DJI Mavic 2 Pro drone, finding a variation of 6.89%. The cost difference between the methodologies was 1,047.73 soles, and the use of the drone proved to be 10 times faster than visual inspection. Finally, it can be said that this study contributes to closing the knowledge gap regarding the use of smart technologies for better pavement management on local roads, so that the actors in charge of the roads can make decisions based on science and thus con-tribute to the well-being of the population.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
