Engine Fault Detection System (Autoguard)
Year: 2024
Type: article
Abstract: This report presents the development of a mobile application named AutoGuard, which serves as a comprehensive anomaly detection system specifically designed for the automotive industry. AutoGuard utilizes advanced machine learning techniques, including statistical modeling, to analyze data collected from various sensors in a vehicle’s engine. The application not only detects potential faults but also provides real-time diagnostics by processing and visualizing the information in a user-friendly format. Extensive testing and analysis demonstrate the system’s ability to enhance vehicle safety and maintenance efficiency, making it a valuable tool for both drivers and automotive professionals.
Author: Timon Trifonov
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404482626