In Saudi Arabia, traffic accidents are a major source of death and serious injury, with a significantly impacting public safety, emergency response efficiency, and the local economy. The city of Bisha faces challenges with managing emergency response effectively. The goal of this project is to develop a smart accident management system that improves accident detection, emergency response, and system implementation efficiency by utilizing Geographic Information Systems (GIS), Internet of Things (IoT) sensors, and AI-driven automation in conjunction with project management concepts. The suggested system combines GPS and GSM modules with vibration and ultrasonic sensors to relay exact location data, identify accidents in real time, and automatically notify emergency services without the need for human participation. The Critical Path Method (CPM) and other project management approaches were used to identify critical activities to avoid delays and to ensure efficient scheduling and resource allocation. The project was found to take 28 weeks in total. The system’s design and functionality were evaluated using simulation tools like Arena, Proteus, and SolidWorks. System sustainability and dependability were improved by implementing risk management techniques like Fault Tree Analysis (FTA) and Failure Mode and Effects Analysis (FMEA). The cost-benefit analysis used to determine economic feasibility showed a 1.35-year payback period. The study confirms two key findings: (1) applying CPM optimizes project scheduling and deployment efficiency, and (2) the system is economically viable, demonstrating financial sustainability and long-term benefits The goal of this intelligent system is to enhance emergency response management by integrating cutting-edge technologies and carrying out projects effectively.