AI-Driven App Management: Enhancing Device Optimization and Digital Wellbeing
This article investigates the integration of machine learning techniques for intelligent application management in mobile devices, addressing the challenges of application overload and its impact on device performance and user wellbeing. The article presents a comprehensive framework that combines resource optimization with digital well-being considerations, implementing on-device processing through conditional approximate neural networks. The system analyzes user behavior patterns, resource consumption metrics, and psychological factors to provide personalized recommendations for application management. By incorporating insights from technical performance analysis and user behavior studies, the framework demonstrates significant improvements in device efficiency, user productivity, and digital well-being while maintaining high user satisfaction rates through transparent and explainable AI implementations.
Authors
- Kamal Gupta (ORCID: https://orcid.org/0000-0002-2440-9033)
Institutions
- University of Birmingham (GB)
Publication Details
- Journal
- International Journal of Scientific Research in Computer Science Engineering and Information Technology
- Published
- 2025-03-06
- DOI
- https://doi.org/10.32628/cseit25112375
- Primary Topic
- Green IT and Sustainability
- Type
- article
- Field-Weighted Citation Impact
- 0.00