Can-Based Intelligent Vehicle Automation And Real-Time Accident Detection With Automatic Alert SystemID: 2325 Abstract :Modern Vehicular Systems Increasingly Rely On Automation And Intelligent Monitoring To Enhance Safety, Reduce Human Error, And Ensure Rapid Emergency Response. Conventional Accident Detection Mechanisms Depend On Manual Reporting, Resulting In Delayed Assistance And Increased Fatalities. This Research Presents A Control Area Network (CAN)–based Vehicle Automation And Accident Alert System That Integrates Sensors, Microcontrollers, And Communication Modules To Detect Collisions, Monitor Vehicle Parameters, And Automatically Transmit Emergency Notifications. The System Utilizes Accelerometers, Vibration Sensors, And Onboard Diagnostics To Detect Abnormalities, While CAN Provides Reliable, High-speed, Fault-tolerant Communication Within The Vehicle. Upon Detecting An Accident, The System Triggers Automatic Alerts Containing Vehicle ID, GPS Location, And Status Information To Emergency Contacts Or Authorities. Additionally, Automation Features Such As Speed Monitoring, Obstacle Detection, And Automatic Braking Enhance Driver Safety. The Integration Of CAN Ensures Robustness, Low Latency, And Reduced Wiring Complexity. The Proposed System Offers A Cost-effective, Scalable Solution For Intelligent Transportation Systems And Next-generation Automotive Safety Design. Keywords: Control Area Network (CAN), Intelligent Vehicle Automation, Accident Detection System, Automatic Alert Notification, Vehicle Safety Monitoring, GPS-Based Emergency Alert, Accelerometer Sensor, Vibration Sensor, Onboard Diagnostics (OBD), Intelligent Transportation Systems (ITS). |
Published:31-3-2026 Issue:Vol. 26 No. 3 (2026) Page Nos:1172-1179 Section:Articles License:This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. How to CiteS. Imran Basha, Gundala Sri Hari, Kandlaguduru Chiranjeevi, Maridi Naga Vignesh, Puchakayalamada Kalyan, Can-Based Intelligent Vehicle Automation And Real-Time Accident Detection With Automatic Alert System , 2026, International Journal of Engineering Sciences and Advanced Technology, 26(3), Page 1172-1179, ISSN No: 2250-3676. |