Nowadays safety and security are significant challenges for emergency users. In emergency situations such as acid burning, kidnapping, robbery, theft, and so on, there is no assurance for the safety of women, old aged people, and children in a real-world environment. Such kinds of situations have created an intense fear and anxiety among women, old-aged people, and children. In this work, agent-based framework for providing real time services to users using machine learning approach for emergency contexts is proposed. The proposed system monitors diverse emergency situations and also providing emergency services. In this paper, the proposed system for emergency users would work constantly and replace human patrols. Finally, it evaluates the performance parameters in terms of data processing time, throughput, and computation overhead.