Abstract: Engine downsizing and boosting have been some of the most widely used strategies for improving engine efficiency in recent years. Several studies have offered significant departures from on-road pre-ignition to steady-state engine laboratory studies, necessitating more robust data-driven diagnostic tools that can identify pre-ignition events in real world environments. The goal of this study is to apply deep neural networks for pre-ignition (PI) detection, based on scientific data obtained from less expensive sensors (like...