AI-Based Mobile Coaching Architectures for Driver Behavior and Road Safety: A Systematic Mapping and Design Framework.
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| Title: | AI-Based Mobile Coaching Architectures for Driver Behavior and Road Safety: A Systematic Mapping and Design Framework. |
|---|---|
| Authors: | Hilario, Manuel1 fhilario@unfv.edu.pe, Paredes, Pervis1, Maquera, Henry2, Martínez, Shirley1, Velasque, Jhosep1 |
| Source: | International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 8, p149-171. 23p. |
| Subjects: | Behavior modification, Road safety measures, Data protection, Motor vehicle driving, Software architecture, Mobile operating systems |
| Abstract: | A systematic mapping of artificial intelligence (AI)-based mobile driver coaching for behavior change and road safety in land transportation has been conducted following PRISMA, resulting in nine empirical studies (n = 9). The evidence is organized through a taxonomy covering intervention goals, AI techniques, data sources, deployment patterns, outcome and engagement metrics, and privacy/dependability safeguards. Across the mapped interventions, a substantial share targets specific risky behaviors, particularly phone-related distraction, reporting relative reductions of up to 21% versus controls in controlled evaluations. Deployment designs are predominantly hybrid, combining on-device inference for timely detection with server-side components for aggregation and program features. Based on the extracted evidence, a system-oriented design framework and practical guidelines are proposed to support researchers and mobile system designers in selecting architectures and evaluation metrics for interactive driver coaching. Key limitations include heterogeneous outcome definitions and predominantly short- to medium-term follow-up, which constrain comparability and generalization across settings. [ABSTRACT FROM AUTHOR] |
| Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 193266435 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: AI-Based Mobile Coaching Architectures for Driver Behavior and Road Safety: A Systematic Mapping and Design Framework. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hilario%2C+Manuel%22">Hilario, Manuel</searchLink><relatesTo>1</relatesTo><i> fhilario@unfv.edu.pe</i><br /><searchLink fieldCode="AR" term="%22Paredes%2C+Pervis%22">Paredes, Pervis</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Maquera%2C+Henry%22">Maquera, Henry</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Martínez%2C+Shirley%22">Martínez, Shirley</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Velasque%2C+Jhosep%22">Velasque, Jhosep</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Interactive+Mobile+Technologies%22">International Journal of Interactive Mobile Technologies</searchLink>. 2026, Vol. 20 Issue 8, p149-171. 23p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Behavior+modification%22">Behavior modification</searchLink><br /><searchLink fieldCode="DE" term="%22Road+safety+measures%22">Road safety measures</searchLink><br /><searchLink fieldCode="DE" term="%22Data+protection%22">Data protection</searchLink><br /><searchLink fieldCode="DE" term="%22Motor+vehicle+driving%22">Motor vehicle driving</searchLink><br /><searchLink fieldCode="DE" term="%22Software+architecture%22">Software architecture</searchLink><br /><searchLink fieldCode="DE" term="%22Mobile+operating+systems%22">Mobile operating systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: A systematic mapping of artificial intelligence (AI)-based mobile driver coaching for behavior change and road safety in land transportation has been conducted following PRISMA, resulting in nine empirical studies (n = 9). The evidence is organized through a taxonomy covering intervention goals, AI techniques, data sources, deployment patterns, outcome and engagement metrics, and privacy/dependability safeguards. Across the mapped interventions, a substantial share targets specific risky behaviors, particularly phone-related distraction, reporting relative reductions of up to 21% versus controls in controlled evaluations. Deployment designs are predominantly hybrid, combining on-device inference for timely detection with server-side components for aggregation and program features. Based on the extracted evidence, a system-oriented design framework and practical guidelines are proposed to support researchers and mobile system designers in selecting architectures and evaluation metrics for interactive driver coaching. Key limitations include heterogeneous outcome definitions and predominantly short- to medium-term follow-up, which constrain comparability and generalization across settings. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3991/ijim.v20i08.59843 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 23 StartPage: 149 Subjects: – SubjectFull: Behavior modification Type: general – SubjectFull: Road safety measures Type: general – SubjectFull: Data protection Type: general – SubjectFull: Motor vehicle driving Type: general – SubjectFull: Software architecture Type: general – SubjectFull: Mobile operating systems Type: general Titles: – TitleFull: AI-Based Mobile Coaching Architectures for Driver Behavior and Road Safety: A Systematic Mapping and Design Framework. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hilario, Manuel – PersonEntity: Name: NameFull: Paredes, Pervis – PersonEntity: Name: NameFull: Maquera, Henry – PersonEntity: Name: NameFull: Martínez, Shirley – PersonEntity: Name: NameFull: Velasque, Jhosep IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 04 Text: 2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 18657923 Numbering: – Type: volume Value: 20 – Type: issue Value: 8 Titles: – TitleFull: International Journal of Interactive Mobile Technologies Type: main |
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