Object detection YOLO-v4 based smart car system with an integrated Virtual Assistant

Abstract

Car accidents are a serious social problem that often results in both life loss and financial loss. Most car accidents are caused by a lack of safe distance between cars and also the awareness of the driver. To relieve this issue, in this paper we propose a real-time object detection and safety system. The proposed system consists of two units: a real-time object detection unit and a safety alarm unit. The system is supposed to apply in a normal driving scenario. As for the safety alarm module, it consists of three states: to detect the object; to calculate the safety factor; to determine the driving conditions. To justify the proposed system, a real experiment is conducted. The results show that the system can appropriately signify driving states: safe, dangerous, and warning. By the given experimental results, it implies that the system is feasible and applicable in real-time applications. The objective of this project is to detect objects in real-time and pass information to the user based on the data taken by object detection. The information can be provided to warn the user or to just inform the user based on the result of the sensors. The YOLO algorithm helps to design the output of the sensor based on the necessity of the user. The google assistant allows the user to provide voice commands. The car is integrated with all the above-mentioned.