Architecture for the 15-Minute City

Bibliographic Details
Main Author: Melo, Leonardo
Publication Date: 2021
Other Authors: Cruz, Nuno, Datia, Nuno
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.21/13805
Summary: Finding a new home in a large city has increasingly become more complex, as people are concerned with not only the estate itself but also with its surroundings. The 15-Minute City concept, thinks of cities as a way to ensure that their residents within a 15-minute radius, can fulfill six essential functions: home, work, commerce, health care, education, and entertainment; which varies according to a chosen travel mode. To help people find properties that would fit them according to this concept, we have built an application that aims to provide an intuitive user interface that guides the user through the important decision of buying a house. To present relevant information to the user, we gathered information from three relevant sources, each with its unique challenges. The first source is estate data, extracted from the websites of local real estate agencies; second, city data, with points of interest relevant to the six essential functions mentioned previously; and at last, the user data provided by the user itself through our profile system which lets us understand his needs. System-wise, we built a reliable application following the microservices architecture guidelines, which future proofs our solution by segregating each part of the project and allowing it to scale easily, development and feature wise. The application scrapes, ingests, transforms and stores data regularly. The complete infrastructure is containerized using Docker and orchestrated by Kubernetes. With this application, we provided a scalable solution that allows users to select the best real estate taking into consideration the surrounding environment, tailored to their day-to-day needs, something that, as far as we know, is a novelty on real estate agency websites.
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spelling Architecture for the 15-Minute City15-Minute CitiesCloud computingGeographical systemsDistributed systemsMicroservicesFinding a new home in a large city has increasingly become more complex, as people are concerned with not only the estate itself but also with its surroundings. The 15-Minute City concept, thinks of cities as a way to ensure that their residents within a 15-minute radius, can fulfill six essential functions: home, work, commerce, health care, education, and entertainment; which varies according to a chosen travel mode. To help people find properties that would fit them according to this concept, we have built an application that aims to provide an intuitive user interface that guides the user through the important decision of buying a house. To present relevant information to the user, we gathered information from three relevant sources, each with its unique challenges. The first source is estate data, extracted from the websites of local real estate agencies; second, city data, with points of interest relevant to the six essential functions mentioned previously; and at last, the user data provided by the user itself through our profile system which lets us understand his needs. System-wise, we built a reliable application following the microservices architecture guidelines, which future proofs our solution by segregating each part of the project and allowing it to scale easily, development and feature wise. The application scrapes, ingests, transforms and stores data regularly. The complete infrastructure is containerized using Docker and orchestrated by Kubernetes. With this application, we provided a scalable solution that allows users to select the best real estate taking into consideration the surrounding environment, tailored to their day-to-day needs, something that, as far as we know, is a novelty on real estate agency websites.RCIPLMelo, LeonardoCruz, NunoDatia, Nuno2021-09-27T11:22:40Z2021-09-152021-09-15T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10400.21/13805enginfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-12T07:58:35Zoai:repositorio.ipl.pt:10400.21/13805Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T19:52:40.747917Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Architecture for the 15-Minute City
title Architecture for the 15-Minute City
spellingShingle Architecture for the 15-Minute City
Melo, Leonardo
15-Minute Cities
Cloud computing
Geographical systems
Distributed systems
Microservices
title_short Architecture for the 15-Minute City
title_full Architecture for the 15-Minute City
title_fullStr Architecture for the 15-Minute City
title_full_unstemmed Architecture for the 15-Minute City
title_sort Architecture for the 15-Minute City
author Melo, Leonardo
author_facet Melo, Leonardo
Cruz, Nuno
Datia, Nuno
author_role author
author2 Cruz, Nuno
Datia, Nuno
author2_role author
author
dc.contributor.none.fl_str_mv RCIPL
dc.contributor.author.fl_str_mv Melo, Leonardo
Cruz, Nuno
Datia, Nuno
dc.subject.por.fl_str_mv 15-Minute Cities
Cloud computing
Geographical systems
Distributed systems
Microservices
topic 15-Minute Cities
Cloud computing
Geographical systems
Distributed systems
Microservices
description Finding a new home in a large city has increasingly become more complex, as people are concerned with not only the estate itself but also with its surroundings. The 15-Minute City concept, thinks of cities as a way to ensure that their residents within a 15-minute radius, can fulfill six essential functions: home, work, commerce, health care, education, and entertainment; which varies according to a chosen travel mode. To help people find properties that would fit them according to this concept, we have built an application that aims to provide an intuitive user interface that guides the user through the important decision of buying a house. To present relevant information to the user, we gathered information from three relevant sources, each with its unique challenges. The first source is estate data, extracted from the websites of local real estate agencies; second, city data, with points of interest relevant to the six essential functions mentioned previously; and at last, the user data provided by the user itself through our profile system which lets us understand his needs. System-wise, we built a reliable application following the microservices architecture guidelines, which future proofs our solution by segregating each part of the project and allowing it to scale easily, development and feature wise. The application scrapes, ingests, transforms and stores data regularly. The complete infrastructure is containerized using Docker and orchestrated by Kubernetes. With this application, we provided a scalable solution that allows users to select the best real estate taking into consideration the surrounding environment, tailored to their day-to-day needs, something that, as far as we know, is a novelty on real estate agency websites.
publishDate 2021
dc.date.none.fl_str_mv 2021-09-27T11:22:40Z
2021-09-15
2021-09-15T00:00:00Z
dc.type.driver.fl_str_mv conference object
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.21/13805
url http://hdl.handle.net/10400.21/13805
dc.language.iso.fl_str_mv eng
language eng
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