Abstract: This paper talks about a précised safety model incorporating elements of Artificial Intelligence for real-time violence detection along with Alert System. This model utilizes the advancements in technology to rapidly respond to any potential violent assault incident. When these technologies are further developed, it also increases the possibilities of how they could be used in future to safeguard schools, public area safety, personal safety, and social stability. Numerous researches and trials have been conducted to counter violence with the passage of time that includes the installations of surveillance systems for warning or alerting to violent activities. Its main objective is to get surveillance systems to automatically annotate the violence activities and issue any Warning/Alerts. For this purpose, first of all the system proceeds with the process of foregrounding a person in each frame, then relevant frames are extracted and irrelevant are ignored, after this violent pattern is identified by the trained model is detected, and end up saving these frames as images. The image is then enhanced and the corresponding details like time and location are transmitted as an alert via Telegram app. The proposed technique is essentially based on deep learning for automatic violence detection using Convolutional Neural networks (CNN). For this diagnosis, a light weight pre-trained model, MobileNetV2, is used to ensure better accuracy than an independent CNN which requires massive computation time and reduced precision.