Numerous research efforts are currently directed toward developing self-driving electric vehicles that rely on AI. Proper lane markings, standardized road signs, and road marking formats are important for better lane detection, object detection on roads, and road sign detection for AI-driven Autonomous EV cars. However, creating these markings on roads or floors is challenging as it consumes more time, is expensive, and requires more personnel. Furthermore, if self-driving cars use the road, markings need to be maintained periodically. An automated process for painting and maintaining road lane markings would efficiently deal with this challenge. The cost, time, and manpower required to mark roads can be reduced by using an autonomous road-marking robot. The proposed solution centers on the implementation of image processing in OpenCV on a scaled-down prototype autonomous wheeled robot built using Raspberry Pi and Arduino to draw road markings parallel to the detected road edge with minimal intervention. The primary focus of this conference paper is on the detection of road edges using a camera module, as it represents a crucial aspect of the problem. By emphasizing the importance of road edge detection, this paper aims to contribute to the development of more efficient and autonomous road-marking technologies.