To study the variation characteristics of sheet resistance of thin film samples under variable temperature conditions, a device integrating a Bayesian optimization fuzzy PID temperature control system and a four-probe method was designed. The Bayesian optimization algorithm was used to find the optimal parameter combination for the fuzzy controller, significantly improving the temperature control accuracy of the system and greatly reducing the experimental cost of the parameter optimization process. A highly stable constant current source circuit and a high-precision digital voltmeter were designed for the four-probe system to ensure stable current supply and accurate voltage measurement even when the resistance of the thin film changes by two to three orders of magnitude. Through an efficient two-way communication protocol between the embedded system and the host computer, the duty cycle of PWM, temperature and voltage data were synchronously transmitted in real time, achieving high-precision temperature control and real-time calculation of the sheet resistance of the thin film samples.