The Fourth Industrial Revolution (4IR) has transformed manufacturing and maintenance through advanced technologies, including the Internet of Things (IoT), cloud computing, and Decision Support Systems (DSS). In vehicle maintenance, IoT enables real-time data collection from Electronic Control Units to facilitate predictive and periodic maintenance, enhancing reliability and efficiency. This study develops an IoT-based DSS for periodic vehicle maintenance, focusing on data from vehicle sensors to optimize maintenance intervals based on mileage and component conditions. The system was designed using a web server and database infrastructure, integrated with Application Programming Interfaces to enable real-time communication between the vehicle’s sensors and a web dashboard. The dashboard displays component statuses and provides maintenance recommendations. Testing involved function and performance evaluations on data communication between an OBD-II scanner, IoT gateway, and web dashboard. The system
reads real-time vehicle data effectively, provides maintenance recommendations based on pre-set DSS rules, and updates component status on the web interface. Tests confirmed synchronization between sensor readings and displayed data, with a response delay under 500 ms, meeting real-time system criteria. The IoT-based DSS for vehicle maintenance proved effective in automating maintenance scheduling, providing users with timely and accurate recommendations. This system promotes efficient and proactive vehicle maintenance, aligning with 4IR goals by enhancing operational reliability through real-time data integration and automated decision support.