CAMS-X: Extending the Context-Aware Mobile Systems Framework for Cross-Platform Development with Ionic
| cic.institucionOrigen | Laboratorio de Investigación y Formación en Informática Avanzada (LIFIA) | |
| cic.isFulltext | SI | |
| cic.isPeerReviewed | SI | |
| cic.lugarDesarrollo | Laboratorio de Investigación y Formación en Informática Avanzada (LIFIA) | |
| cic.parentType | Objeto de conferencia | |
| cic.version | Aceptada | |
| dc.date.accessioned | 2026-03-06T13:25:18Z | |
| dc.date.available | 2026-03-06T13:25:18Z | |
| dc.identifier.uri | https://digital.cic.gba.gob.ar/handle/11746/12659 | |
| dc.title | CAMS-X: Extending the Context-Aware Mobile Systems Framework for Cross-Platform Development with Ionic | en |
| dc.type | Documento de conferencia | |
| dcterms.abstract | The rapid evolution of mobile applications has led to an increasing demand for solutions that can operate seamlessly across multiple platforms, including iOS, Android, and web, while maintaining context-aware capabilities. In response to this need, we present CAMS-X, an extension of the Context-Aware Mobile Systems (CAMS) framework, designed to simplify the development of cross-platform, context-aware applications using Ionic. CAMS-X leverages a Domain-Specific Language (DSL) for modeling contextual information and business rules, while automating code generation for multiplatform applications through Ionic and Angular. The framework integrates cloud services such as Azure Maps for geolocation, IoT Hub for sensor data management, and Twilio for contextual notifications, ensuring consistent functionality across platforms. Additionally, CAMS-X employs Infrastructure-as-Code (IaC) tools like Pulumi and Terraform to automate cloud resource provisioning, reducing deployment complexity and improving scalability. A case study on package tracking demonstrates CAMS-X's ability to dynamically adjust application behavior in real time based on contextual data from IoT sensors and geolocation services. Evaluation results show a 40% reduction in development time compared to traditional methods, with support for up to 10,000 IoT devices simultaneously. CAMS-X represents a significant advancement in the development of intelligent, cross-platform mobile applications, offering a robust and flexible solution for industries such as logistics, smart cities, and real-time monitoring. Future work includes expanding support for additional IoT capabilities, integrating AI-driven decision-making tools, and further enhancing the DSL to support more complex use cases. | en |
| dcterms.creator.author | Gómez-Torres, Estevan Ricardo | |
| dcterms.creator.author | Bernis, Christian P. | |
| dcterms.creator.author | Valdivieso, Wellington | |
| dcterms.creator.author | Baldeón Andrade, Alexander Omar | |
| dcterms.creator.author | Challiol, Cecilia | |
| dcterms.identifier.other | DOI: 10.1007/978-981-96-8399-4_41 | |
| dcterms.identifier.other | ISBN: 978-981-96-8399-4 | |
| dcterms.isPartOf.item | ICT for Intelligent Systems. ICTIS 2025 | |
| dcterms.isPartOf.series | International Conference on Information and Communication Technology for Intelligent Systems. ICTIS 2025 (Nueva York, 23 y 24 de mayo de 2025) | |
| dcterms.issued | 2025 | |
| dcterms.language | Inglés | |
| dcterms.license | Attribution-NonCommercial-NoDerivatives 4.0 International (BY-NC-ND 4.0) | |
| dcterms.subject | Context-Aware Systems | en |
| dcterms.subject | Cross-Platform Development | en |
| dcterms.subject | Iconic | en |
| dcterms.subject | Model-Driven Developmen | en |
| dcterms.subject | IoT | en |
| dcterms.subject | Azure Maps | en |
| dcterms.subject | DSL | en |
| dcterms.subject | Multiplatform Applications | en |
| dcterms.subject.materia | Ciencias de la Computación e Información |
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