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AI-Driven App Management: Enhancing Device Optimization and Digital Wellbeing

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  • Kamal Gupta

Abstract

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.

Suggested Citation

  • Kamal Gupta, 2025. "AI-Driven App Management: Enhancing Device Optimization and Digital Wellbeing," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(2), pages 327-335, March.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i2:id:1099
    DOI: 10.32628/CSEIT25112375
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25112375
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