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AI-Driven Innovations in System Reliability, Government Automation, and Personalized Learning

Author

Listed:
  • Vivien A. Agustin

    (Graduate School Department La Consolacion University, Bulihan, City of Malolos, Bulacan, Philippines)

  • Jonilo Mababa

    (Graduate School Department La Consolacion University, Bulihan, City of Malolos, Bulacan, Philippines)

  • Vilma A. Dela Cruz

    (Graduate School Department Pamantasan ng Lungod ng Maynila, Intramuros Manila, Philippines)

  • Edwin C. Agustin

    (Graduate School Department Pamantasan ng Lungod ng Maynila, Intramuros Manila, Philippines)

  • Vanessa A. Diaz

    (Civil-Military Operations Regiment CMOR Compound Lawton Avenue Fort Bonifacio Taguig City, Philippines)

  • Verona A. Guzman

    (J. Villegas Vocational High School Jacinto St.)

  • Criselle J. Centeno

    (Graduate School Department Pamantasan ng Lungod ng Maynila, Intramuros Manila, Philippines Tondo, Manila, Philippines)

Abstract

This study demonstrates how Generative AI (GenAI) may improve productivity, accuracy, and workflow optimization in a variety of applications, including autonomous snowcat navigation, government report automation, and AI-powered personalized e-learning. AI-powered data visualization and extraction expedites government reporting while lowering human error and intervention. AI-powered path optimization, obstacle recognition, and sensor fusion enhance autonomous snowcat navigation’s adaptability and safety in challenging environments. Machine learning algorithms make predictive analytics, adaptive content, and recommendation systems possible in personalized e-learning, which improves learning results and student engagement. The findings demonstrate how AI can revolutionize complex process automation, enhance decision-making, and boost operational effectiveness. The necessity for ongoing improvements in transparency, equity, and security in AI applications is highlighted by obstacles including algorithmic bias, data privacy issues, and scale constraints.

Suggested Citation

  • Vivien A. Agustin & Jonilo Mababa & Vilma A. Dela Cruz & Edwin C. Agustin & Vanessa A. Diaz & Verona A. Guzman & Criselle J. Centeno, 2025. "AI-Driven Innovations in System Reliability, Government Automation, and Personalized Learning," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 10(3), pages 762-769, March.
    • Handle: RePEc:bjf:journl:v:10:y:2025:i:3:p:762-769
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