The rapid development of the car rental industry demands a more sophisticated, efficient, and safe fleet supervision system. This research aims to design and implement an Internet of Things (IoT)-based monitoring and safety system with live tracking features on rental vehicles. The system incorporates a GPS module for location tracking, an ESP32 S3 microcontroller as a data processing center, as well as a geofencing feature to detect vehicle movements outside of a predetermined operational area. Data is sent and monitored in real-time through the Telegram platform. The test was conducted to analyze the effect of distance on the response time of the data transmission, as well as the relationship between engine rotation (RPM) and engine temperature. The results showed a positive relationship between distance and response time, where the farther the vehicle is from the Base Transceiver Station (BTS), the greater the delay value, with an average response time of 5,402 ms. Meanwhile, the highest engine temperature was recorded at 2000 r/min at 96°C, but the temperature returned to stability at 4000 r/min due to improved cooling efficiency. As an effort to prevent overheating, the system is equipped with a second fan motor that is active in the temperature range of 96°C to 94°C.  Statistical tests using ANOVA One-Way and normality tests showed a significant influence between variables, so that the system designed proved to be effective in improving the supervision and safety of rental vehicles.