The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities

Detalhes bibliográficos
Autor(a) principal: Neves, Fátima Trindade
Data de Publicação: 2024
Outros Autores: Aparicio, Manuela, Neto, Miguel de Castro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/164626
Resumo: Neves, F. T., Aparicio, M., & Neto, M. D. C. (2024). The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities. Applied Sciences, 14(5), 1-40. Article 2209. https://doi.org/10.3390/app14052209 --- This research was funded by FCT—Fundação para a Ciência e Tecnologia, I.P. (Portugal), under research grant UIDB/04152/2020—Centro de Investigação em Gestão de Informação (MagIC). The authors would like to express their gratitude to Confidencial Imobiliário for graciously providing the real estate transactions data that supported this work.
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spelling The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Citiesopen datasmart citiesreal estate predictionsurban developmentartificial intelligencemachine learningeXplainable AIXGBoostOptunahapley additive explanations (SHAP)SDG 8 - Decent Work and Economic GrowthSDG 11 - Sustainable Cities and CommunitiesNeves, F. T., Aparicio, M., & Neto, M. D. C. (2024). The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities. Applied Sciences, 14(5), 1-40. Article 2209. https://doi.org/10.3390/app14052209 --- This research was funded by FCT—Fundação para a Ciência e Tecnologia, I.P. (Portugal), under research grant UIDB/04152/2020—Centro de Investigação em Gestão de Informação (MagIC). The authors would like to express their gratitude to Confidencial Imobiliário for graciously providing the real estate transactions data that supported this work.In the rapidly evolving landscape of urban development, where smart cities increasingly rely on artificial intelligence (AI) solutions to address complex challenges, using AI to accurately predict real estate prices becomes a multifaceted and crucial task integral to urban planning and economic development. This paper delves into this endeavor, highlighting the transformative impact of specifically chosen contextual open data and recent advances in eXplainable AI (XAI) to improve the accuracy and transparency of real estate price predictions within smart cities. Focusing on Lisbon’s dynamic housing market from 2018 to 2021, we integrate diverse open data sources into an eXtreme Gradient Boosting (XGBoost) machine learning model optimized with the Optuna hyperparameter framework to enhance its predictive precision. Our initial model achieved a Mean Absolute Error (MAE) of EUR 51,733.88, which was significantly reduced by 8.24% upon incorporating open data features. This substantial improvement underscores open data’s potential to boost real estate price predictions. Additionally, we employed SHapley Additive exPlanations (SHAP) to address the transparency of our model. This approach clarifies the influence of each predictor on price estimates and fosters enhanced accountability and trust in AI-driven real estate analytics. The findings of this study emphasize the role of XAI and the value of open data in enhancing the transparency and efficacy of AI-driven urban development, explicitly demonstrating how they contribute to more accurate and insightful real estate analytics, thereby informing and improving policy decisions for the sustainable development of smart cities.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNNeves, Fátima TrindadeAparicio, ManuelaNeto, Miguel de Castro2024-03-08T00:00:14Z2024-03-062024-03-06T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article41application/pdfhttp://hdl.handle.net/10362/164626eng2076-3417PURE: 84725919https://doi.org/10.3390/app14052209info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-18T01:44:26Zoai:run.unl.pt:10362/164626Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T04:00:17.463255Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
title The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
spellingShingle The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
Neves, Fátima Trindade
open data
smart cities
real estate predictions
urban development
artificial intelligence
machine learning
eXplainable AI
XGBoost
Optuna
hapley additive explanations (SHAP)
SDG 8 - Decent Work and Economic Growth
SDG 11 - Sustainable Cities and Communities
title_short The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
title_full The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
title_fullStr The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
title_full_unstemmed The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
title_sort The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities
author Neves, Fátima Trindade
author_facet Neves, Fátima Trindade
Aparicio, Manuela
Neto, Miguel de Castro
author_role author
author2 Aparicio, Manuela
Neto, Miguel de Castro
author2_role author
author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv Neves, Fátima Trindade
Aparicio, Manuela
Neto, Miguel de Castro
dc.subject.por.fl_str_mv open data
smart cities
real estate predictions
urban development
artificial intelligence
machine learning
eXplainable AI
XGBoost
Optuna
hapley additive explanations (SHAP)
SDG 8 - Decent Work and Economic Growth
SDG 11 - Sustainable Cities and Communities
topic open data
smart cities
real estate predictions
urban development
artificial intelligence
machine learning
eXplainable AI
XGBoost
Optuna
hapley additive explanations (SHAP)
SDG 8 - Decent Work and Economic Growth
SDG 11 - Sustainable Cities and Communities
description Neves, F. T., Aparicio, M., & Neto, M. D. C. (2024). The Impacts of Open Data and eXplainable AI on Real Estate Price Predictions in Smart Cities. Applied Sciences, 14(5), 1-40. Article 2209. https://doi.org/10.3390/app14052209 --- This research was funded by FCT—Fundação para a Ciência e Tecnologia, I.P. (Portugal), under research grant UIDB/04152/2020—Centro de Investigação em Gestão de Informação (MagIC). The authors would like to express their gratitude to Confidencial Imobiliário for graciously providing the real estate transactions data that supported this work.
publishDate 2024
dc.date.none.fl_str_mv 2024-03-08T00:00:14Z
2024-03-06
2024-03-06T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/164626
url http://hdl.handle.net/10362/164626
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2076-3417
PURE: 84725919
https://doi.org/10.3390/app14052209
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 41
application/pdf
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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