Student Safety Monitoring System Through IOT Sensors For Bullying Prediction

School bullying remains an important issue affecting the safety and well-being of students. This study introduces a novel anti-bullying system that utilizes Internet of Things (IoT) sensors to predict and prevent bullying in educational Settings. The project consists of four main parts: introduction, literature review, proposed methodology, and project timeline with milestones. Through an extensive analysis of bullying in schools, including existing research and empirical data, the study identifies powerful strategies to mitigate such incidents. The proposed system combines voice recognition technology with the Internet of Things, utilizing hardware components such as Raspberry Pi, Arduino and various sensors to detect and respond to bullying. Voice sensors are strategically installed throughout the campus to identify and analyze sensitive speech and distress signals, immediately alerting school authorities for timely intervention. This integrated approach aims to enhance campus safety, ensure the physical safety of students and promote a healthy development environment. The success of the project relies on the joint efforts of schools, students, parents and the wider community to comprehensively address and reduce bullying. This paper Outlines the technical specifications, design, and implementation phases, and critically evaluates the effectiveness and limitations of the system.