An AI-Driven Framework for Automated Human Violence Detection Using Advanced Deep Learning Model and IoT Systems
Vidyarani H J · International Journal for Research in Applied Science and Engineering Technology · 2025
Human violence poses a significant threat to public safety, making its early detection critical in preventing harm and ensuring timely intervention. In today's world, it is a growing necessity that public safety can be achieved through intelligent surveillance systems. In this paper, we propose an AI driven framework on automated human violence detection through the combination of advanced deep learning techniques with IoT technologies. The system relies on YOLO (You Only Look Once) object detection model from processing live video feeds to determining violent actions like fights and assaults. A custom dataset, recorded and augmented by myself, was used to improve model reliability and performance. The framework was able to achieve 92% accuracy, proving its ability to produce real time results at low computational cost. A Telegram bot is used to transmit notifications and alerts instantly, boosting the level of security and intervention in time. The framework is designed for scalability and adaptability, being deployable in offices, schools or public areas. In the future, predictive analytics will be embedded, multi camera support will be added, and by using Cloud storage, system efficiency and scalability will further be enhanced. AI and IoT facilitates smart, responsive violence detection surveillance systems is a transformative piece of this research.