ABSTRACT
Due to the global pandemic of Coronavirus 2019 disease (COVID-19), which began in late 2019, the world has changed and forced all human life to adapt by living in new forms, isolated from the community for both works and learning from their residences. COVID-19 disease undoubtedly has had an impact on the transportation ecosystem. Food, groceries, and even medications are delivered directly from restaurants to customers by deliverers, who can cause exposure and easily infect. Delivery solutions have been proposed and solved through the application of Internet of Things (IoT) knowledge to reduce customer-deliverer exposure. The Internet of Things concept can assist us in developing a mobility object or simulated car that operates without human intervention. The vehicle is programmed to run parallel to the surface of a continuous line, which is referred to as line following. Calibration of the line follower sensor is required to achieve a higher effective tracking accuracy under various conditions, such as line width or rough surface. This research examines and compares how the simulated car behaves when run on various linewidths in preparation for future application and development. © 2022 ACM.