System for location and reservation of parking spaces in the city of Huancayo through a mobile application

The study is based on developing a technological model based on Machine Learning (ML) through a mobile application for searching and reserving parking in real time. It begins by identifying the methodology for implementing the model from the user's perspective in relation to the parking service provided by the host. Then, a prototype of the technological model is created using the Figma prototype design tool. Statistical tests are designed to evaluate the technological model using python code to demonstrate the results, with indicators such as "Parking search time" and "User satisfaction" from 42 users. Data on these indicators were collected before and after the implementation of the technological model. The results show a significant difference in search times and user satisfaction between the technological model and the traditional method of searching for parking. It is concluded that the technological model offers advantages in reducing search time and improving user experience, which simplifies urban life and helps mitigate traffic congestion problems. Promoting development through innovation and the adoption of emerging technologies in the search for parking, with an improvement in urban mobility and in the quality of life of citizens.

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Publication Details

Journal
IET conference proceedings.
Published
2025-03-01
DOI
https://doi.org/10.1049/icp.2025.0529
Primary Topic
Smart Parking Systems Research
Type
article
Field-Weighted Citation Impact
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article

System for location and reservation of parking spaces in the city of Huancayo through a mobile application

Alex Max Crisostomo Meza, Xiomara del Pilar Villantoy Guzman, Keeving Joel Chavez Borja, Ruben Angel Ruiz Parejas
IET conference proceedings.
Smart Parking Systems Research
article

System for location and reservation of parking spaces in the city of Huancayo through a mobile application

Alex Max Crisostomo Meza, Xiomara del Pilar Villantoy Guzman, Keeving Joel Chavez Borja, Ruben Angel Ruiz Parejas
article en

Abstract

The study is based on developing a technological model based on Machine Learning (ML) through a mobile application for searching and reserving parking in real time. It begins by identifying the methodology for implementing the model from the user's perspective in relation to the parking service provided by the host. Then, a prototype of the technological model is created using the Figma prototype design tool. Statistical tests are designed to evaluate the technological model using python code to demonstrate the results, with indicators such as "Parking search time" and "User satisfaction" from 42 users. Data on these indicators were collected before and after the implementation of the technological model. The results show a significant difference in search times and user satisfaction between the technological model and the traditional method of searching for parking. It is concluded that the technological model offers advantages in reducing search time and improving user experience, which simplifies urban life and helps mitigate traffic congestion problems. Promoting development through innovation and the adoption of emerging technologies in the search for parking, with an improvement in urban mobility and in the quality of life of citizens.

IET conference proceedings.Vol. 2024(35)
Universidad Continental (PE)
Sustainable cities and communities
Openalex Percentile: Top 95%
Smart Parking Systems Research
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System for location and reservation of parking spaces in the city of Huancayo through a mobile application — Alex Max Crisostomo Meza, Xiomara del Pilar Villantoy Guzman, et al. · IET conference proceedings. (2025) | TGRS Research Map | TGRS