Vehicle Health Monitoring System for Predictive Maintenance and Safety

The rapid advancement of automotive technology has increased the demand for intelligent vehicle monitoring systems to enhance safety, optimize performance, and reduce unexpected failures. Traditional vehicle maintenance relies on periodic servicing and manual inspections, often leading to delayed fault detection. This paper presents an IoT-enabled realtime vehicle health monitoring system that continuously tracks critical vehicle parameters such as speed, coolant temperature, air temperature, barometric pressure, engine runtime, and throttle position. The system is implemented using Arduino and IoTbased modules to collect real-time sensor data, which is transmitted to ThingSpeak, a cloud-based analytics platform. Users can visualize vehicle diagnostics through animated gauges and graphical dashboards while receiving alerts in case of anomalies. By integrating IoT technology into vehicle diagnostics, this system enables predictive maintenance, enhances vehicle safety, and optimizes operational efficiency. The proposed solution benefits individual vehicle owners, fleet management systems, and the automotive insurance industry by providing data-driven insights for performance analysis and proactive fault prevention.