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VOL. 10, ISSUE 3 (2025)
Real-time AI solutions for monitoring and preventing bullying in Educational Institutions
Authors
Sunita Ganesh Satpute, Gopale Tejaswini Rajeshwar
Abstract
In recent years, bullying in educational
institutions has become a significant concern, necessitating advanced
technological solutions for realtime monitoring and prevention. This paper
proposes an AI-driven framework that leverages machine learning, natural
language processing (NLP), and computer vision to detect and mitigate bullying
incidents in schools and colleges. The system integrates surveillance cameras,
voice recognition, and social media analysis to identify verbal, physical, and
cyberbullying behaviors. Utilizing deep learning models, the framework can
analyze facial expressions, body language, and speech patterns to recognize
distress signals and aggressive actions. Additionally, a predictive analytics
module assesses historical data to identify at-risk individuals and suggest
proactive interventions. The proposed solution also includes an alert mechanism
that notifies school authorities and counselors in real time, enabling
immediate intervention and support for victims. By automating the detection and
prevention process, this AI-powered system enhances the overall safety of
educational environments, fostering a culture of respect and well-being among
students. This research aims to bridge the gap between technology and
education, ensuring a proactive approach to bullying prevention while
maintaining ethical considerations regarding privacy and data security.
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Pages:48-51
How to cite this article:
Sunita Ganesh Satpute, Gopale Tejaswini Rajeshwar "Real-time AI solutions for monitoring and preventing bullying in Educational Institutions". International Journal of Advanced Scientific Research, Vol 10, Issue 3, 2025, Pages 48-51
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