Using open data to quantify accessibility to multiple public services: The study case of Lima

Leibnitz Pavel Rojas-Bustamante; Hugo Alatrista-Salas; Miguel Nunez-Del-Prado; Joseph Chamorro

doi:10.1109/INTERCON52678.2021.9532730

Using open data to quantify accessibility to multiple public services: The study case of Lima

Leibnitz Pavel Rojas-Bustamante
, Hugo Alatrista-Salas
, Miguel Nunez-Del-Prado
, Joseph Chamorro

Universidad del Pacífico

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

Resumen

In recent years, accessibility has been widely studied in different domains, like transportation, health, governmental services, parks, and jobs. However, these studies present limitations regarding the number of analyzed services and the limited data access. Therefore, we propose a new accessibility metric to solve both problems, considering six different public services using open data from Open Street Maps. The idea behind this approach is to group deprived zones from public services access. We perform our study in Lima city, which is one of the most populated cities in South America.

Idioma original	Inglés
Título de la publicación alojada	Proceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781665412216
DOI	https://doi.org/10.1109/INTERCON52678.2021.9532730
Estado	Publicada - 5 ago. 2021
Evento	IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021 - Virtual, Lima, Perú Duración: 5 ago. 2021 → 7 ago. 2021 Número de conferencia: 28th

Conferencia

Conferencia	IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021
País/Territorio	Perú
Ciudad	Virtual, Lima
Período	5/08/21 → 7/08/21

Nota bibliográfica

Publisher Copyright:
© 2021 IEEE.

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 9: Industria, innovación e infraestructura
ODS 11: Ciudades y comunidades sostenibles
ODS 16: Paz, justicia e instituciones sólidas
ODS 17: Alianzas para lograr los objetivos

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10.1109/INTERCON52678.2021.9532730

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Rojas-Bustamante, L. P., Alatrista-Salas, H., Nunez-Del-Prado, M., & Chamorro, J. (2021). Using open data to quantify accessibility to multiple public services: The study case of Lima. En Proceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INTERCON52678.2021.9532730

Rojas-Bustamante, Leibnitz Pavel ; Alatrista-Salas, Hugo ; Nunez-Del-Prado, Miguel et al. / Using open data to quantify accessibility to multiple public services : The study case of Lima. Proceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021. Institute of Electrical and Electronics Engineers Inc., 2021.

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abstract = "In recent years, accessibility has been widely studied in different domains, like transportation, health, governmental services, parks, and jobs. However, these studies present limitations regarding the number of analyzed services and the limited data access. Therefore, we propose a new accessibility metric to solve both problems, considering six different public services using open data from Open Street Maps. The idea behind this approach is to group deprived zones from public services access. We perform our study in Lima city, which is one of the most populated cities in South America. ",

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Rojas-Bustamante, LP, Alatrista-Salas, H, Nunez-Del-Prado, M & Chamorro, J 2021, Using open data to quantify accessibility to multiple public services: The study case of Lima. En Proceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021. Institute of Electrical and Electronics Engineers Inc., IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021, Virtual, Lima, Perú, 5/08/21. https://doi.org/10.1109/INTERCON52678.2021.9532730

Using open data to quantify accessibility to multiple public services: The study case of Lima. / Rojas-Bustamante, Leibnitz Pavel; Alatrista-Salas, Hugo; Nunez-Del-Prado, Miguel et al.
Proceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021. Institute of Electrical and Electronics Engineers Inc., 2021.

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

TY - GEN

T1 - Using open data to quantify accessibility to multiple public services

T2 - IEEE International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021

AU - Rojas-Bustamante, Leibnitz Pavel

AU - Alatrista-Salas, Hugo

AU - Nunez-Del-Prado, Miguel

AU - Chamorro, Joseph

N1 - Conference code: 28th

PY - 2021/8/5

Y1 - 2021/8/5

N2 - In recent years, accessibility has been widely studied in different domains, like transportation, health, governmental services, parks, and jobs. However, these studies present limitations regarding the number of analyzed services and the limited data access. Therefore, we propose a new accessibility metric to solve both problems, considering six different public services using open data from Open Street Maps. The idea behind this approach is to group deprived zones from public services access. We perform our study in Lima city, which is one of the most populated cities in South America.

AB - In recent years, accessibility has been widely studied in different domains, like transportation, health, governmental services, parks, and jobs. However, these studies present limitations regarding the number of analyzed services and the limited data access. Therefore, we propose a new accessibility metric to solve both problems, considering six different public services using open data from Open Street Maps. The idea behind this approach is to group deprived zones from public services access. We perform our study in Lima city, which is one of the most populated cities in South America.

KW - accessibility

KW - machine learning

KW - open data

KW - Public service

UR - https://www.scopus.com/pages/publications/85116236632

UR - https://www.mendeley.com/catalogue/6f081370-19e3-3c5a-be27-e9c5db532388/

U2 - 10.1109/INTERCON52678.2021.9532730

DO - 10.1109/INTERCON52678.2021.9532730

M3 - Conference contribution

AN - SCOPUS:85116236632

BT - Proceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 5 August 2021 through 7 August 2021

ER -

Rojas-Bustamante LP, Alatrista-Salas H, Nunez-Del-Prado M, Chamorro J. Using open data to quantify accessibility to multiple public services: The study case of Lima. En Proceedings of the 2021 IEEE 28th International Conference on Electronics, Electrical Engineering and Computing, INTERCON 2021. Institute of Electrical and Electronics Engineers Inc. 2021 doi: 10.1109/INTERCON52678.2021.9532730

Using open data to quantify accessibility to multiple public services: The study case of Lima

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