Promoting sustainable and personalized travel behaviors while preserving data privacy
Cities worldwide have agreed on ambitious goals regarding carbon neutrality. To do so, policymakers seek ways to foster smarter and cleaner transportation solutions. However, citizens lack awareness of their carbon footprint and of greener mobility alternatives such as public transports. With this,...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Transportation Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666691X24000125 |
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| author | Cláudia Brito Noela Pina Tânia Esteves Ricardo Vitorino Inês Cunha João Paulo |
| author_facet | Cláudia Brito Noela Pina Tânia Esteves Ricardo Vitorino Inês Cunha João Paulo |
| author_sort | Cláudia Brito |
| collection | DOAJ |
| description | Cities worldwide have agreed on ambitious goals regarding carbon neutrality. To do so, policymakers seek ways to foster smarter and cleaner transportation solutions. However, citizens lack awareness of their carbon footprint and of greener mobility alternatives such as public transports. With this, three main challenges emerge: (i) increase users’ awareness regarding their carbon footprint, (ii) provide personalized recommendations and incentives for using sustainable transportation alternatives and, (iii) guarantee that any personal data collected from the user is kept private.This paper addresses these challenges by proposing a new methodology. Created under the FranchetAI project, the methodology combines federated Artificial Intelligence (AI) and Greenhouse Gas (GHG) estimation models to calculate the carbon footprint of users when choosing different transportation modes (e.g., foot, car, bus). Through a mobile application that keeps the privacy of users’ personal information, the project aims at providing detailed reports to inform citizens about their impact on the environment, and an incentive program to promote the usage of more sustainable mobility alternatives. |
| format | Article |
| id | doaj-art-0551bab7c4b64ca9b7be515303b10d7e |
| institution | DOAJ |
| issn | 2666-691X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Transportation Engineering |
| spelling | doaj-art-0551bab7c4b64ca9b7be515303b10d7e2025-08-20T02:39:50ZengElsevierTransportation Engineering2666-691X2025-03-011910023710.1016/j.treng.2024.100237Promoting sustainable and personalized travel behaviors while preserving data privacyCláudia Brito0Noela Pina1Tânia Esteves2Ricardo Vitorino3Inês Cunha4João Paulo5INESC TEC & Universidade do Minho, R. da Universidade, Braga, 4710-057, Portugal; Corresponding author.Ubiwhere, lda., Travessa Senhor das Barrocas, 38, Aveiro, 3800–075, Portugal; CITTA & University of Coimbra, R. Luís Reis Santos, Coimbra, 3030-788, PortugalINESC TEC & Universidade do Minho, R. da Universidade, Braga, 4710-057, PortugalUbiwhere, lda., Travessa Senhor das Barrocas, 38, Aveiro, 3800–075, PortugalUbiwhere, lda., Travessa Senhor das Barrocas, 38, Aveiro, 3800–075, PortugalINESC TEC & Universidade do Minho, R. da Universidade, Braga, 4710-057, PortugalCities worldwide have agreed on ambitious goals regarding carbon neutrality. To do so, policymakers seek ways to foster smarter and cleaner transportation solutions. However, citizens lack awareness of their carbon footprint and of greener mobility alternatives such as public transports. With this, three main challenges emerge: (i) increase users’ awareness regarding their carbon footprint, (ii) provide personalized recommendations and incentives for using sustainable transportation alternatives and, (iii) guarantee that any personal data collected from the user is kept private.This paper addresses these challenges by proposing a new methodology. Created under the FranchetAI project, the methodology combines federated Artificial Intelligence (AI) and Greenhouse Gas (GHG) estimation models to calculate the carbon footprint of users when choosing different transportation modes (e.g., foot, car, bus). Through a mobile application that keeps the privacy of users’ personal information, the project aims at providing detailed reports to inform citizens about their impact on the environment, and an incentive program to promote the usage of more sustainable mobility alternatives.http://www.sciencedirect.com/science/article/pii/S2666691X24000125Emissions monitoringData privacyArtificial intelligenceSustainable cities and communitiesMultimodal transportation |
| spellingShingle | Cláudia Brito Noela Pina Tânia Esteves Ricardo Vitorino Inês Cunha João Paulo Promoting sustainable and personalized travel behaviors while preserving data privacy Transportation Engineering Emissions monitoring Data privacy Artificial intelligence Sustainable cities and communities Multimodal transportation |
| title | Promoting sustainable and personalized travel behaviors while preserving data privacy |
| title_full | Promoting sustainable and personalized travel behaviors while preserving data privacy |
| title_fullStr | Promoting sustainable and personalized travel behaviors while preserving data privacy |
| title_full_unstemmed | Promoting sustainable and personalized travel behaviors while preserving data privacy |
| title_short | Promoting sustainable and personalized travel behaviors while preserving data privacy |
| title_sort | promoting sustainable and personalized travel behaviors while preserving data privacy |
| topic | Emissions monitoring Data privacy Artificial intelligence Sustainable cities and communities Multimodal transportation |
| url | http://www.sciencedirect.com/science/article/pii/S2666691X24000125 |
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