AI-Driven Crisis Intervention Sysytem For Perintal Mental Health

Authors

  • Gubbala chakradhar B.E Students, Department of Information Technology, ISL Engineering College, Hyderabad, India. Author
  • Mohd ibrahim B.E Students, Department of Information Technology, ISL Engineering College, Hyderabad, India. Author
  • Dr surya Mukhi Associate Professor, Department of Information Technology, ISL Engineering College, Hyderabad, India. Author

DOI:

https://doi.org/10.62647/IJITCE2025V13I2sPP280-284

Keywords:

Perinatal mental health, crisis intervention, artificial intelligence, natural language processing, machine learning, maternal care

Abstract

Combining advanced artificial intelligence with satellite technologies and vessel tracking has transformed oil spill detection in maritime environments. Our research introduces a robust automated system that integrates data from Automatic Identification Systems (AIS) and Synthetic Aperture Radar (SAR) satellites. By leveraging machine learning algorithms, our approach analyzes vessel behaviors, detects anomalies, and verifies spills using high-resolution SAR images. This multi-source method ensures real-time monitoring and rapid response capabilities, significantly reducing detection times while maintaining high accuracy. Through careful dataset augmentation and training with diverse environmental conditions, our system achieves over 97% accuracy, demonstrating its effectiveness in mitigating ecological and economic impacts. This innovative solution not only enhances environmental monitoring but also underscores our commitment to sustainable practices for safeguarding marine ecosystems.

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Published

12-06-2025

How to Cite

AI-Driven Crisis Intervention Sysytem For Perintal Mental Health. (2025). International Journal of Information Technology and Computer Engineering, 13(2s), 280-284. https://doi.org/10.62647/IJITCE2025V13I2sPP280-284