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Lane detection system for the driver of the car is an important issue for the inquiry as a platform for safe driving experience. Implementation of this system is trying to investigate the possibility of traffic accidents, monitor the efficiency of the movement and position of the car contributes to the development of autonomous navigation technology. The purpose of this study is to get the best selection of banks in a better Hough transform technique to detect lane roads using edge detection techniques. For this study, Canny, Sobel and Prewitt edge detection is used as a trial. Selection of the best edge detection was using neural network techniques. Improved Hough Transform is used to extract features of a structured road. Point area near the straight line model adopted to accelerate the speed of calculation data and find the appropriate line. Prior knowledge is used in the process of finding a path to efficiently reduce the Hough space efficiently, thereby increasing the resistance by increasing the processing speed. Experiments provide good results in detecting straight and smooth fair curvature lane on highway even the hallways are painted shadows. Data from the lane highways have been taken in video format. Experiments have been done using an edge detection technique of choice in each scenario, and found that the best method of producing high accuracy of detection is to use intelligent edge detector. In this way, other people will be the best in certain cases scenarios lane highway.

Life Buoy, also known as a life preserver, is a crucial safety tool on board any marine ships. The most common and conventional lifesaver is operated manually to save people from drowning, yet this method poses a risk for both the victim and rescuer. Hence, with the help of current technology, a smart lifebuoy has been developed, whereby the rescuer just operates the lifebuoy using remote control. Yet, the existing smart life buoy system has been found heavy and hard to be operated, especially for women, children, and other people with disabilities.This paper focuses on the development of a lightweight smart life buoy system and its characteristics.  Arduino Uno R3, Arduino Nano, DC motor 775, Transmitter and Receiver kit were the main components used in the development of the lightweight smart life buoy system (LWSLB). The developed LWSLB system was tested at the National Defence University of Malaysia’ swimming pool due to Covid-19 lockdown, and data such as speed, range of remote connection and battery endurance were obtained. It has been found out that the developed LWSLB weighs just 3.5kg overall compared to Brand S which weighs 13.75kg. However, in terms of speed, Brand S proves to be faster at 4.17m/s compared to LWSLB which exhibits a speed of 1.25m/s.