EADD: An Intelligent Edge-Based Anomaly Detection Platform for Car Driving
En-Hau Yeh, Yumin Chen, Phone Lin, Shun‐Ren Yang, Rongxing Lu · 2024
Detecting abnormal driving behavior is crucial for preventing traffic accidents, as they are responsible for a sig-nificant majority of incidents. However, existing methods for detection often come with high costs or execution restrictions. In this paper, we introduce EADD, an Edge-based Anomaly Detection platform for Driving behavior. EADD overcomes these limitations by detecting abnormal driving behavior without the need for additional sensors or restrictions. Additionally, EADD boasts low computational requirements and enables real-time detection on mobile devices like the Raspberry Pi 3 Model B.