Abstract: This study designed and implemented a programmable heating control system coupled with a wireless temperature-sensing stir bar to optimize experimental procedures for Hofmann degradation reactions. The integrated system incorporates Internet of Things (IoT)-based wireless temperature monitoring, a combined heating/cooling device, and Proportional-Integral-Derivative (PID) algorithm-based precision temperature control to improve the success rate and product purity in temperature-sensitive organic chemistry experiments. The wireless temperature sensing technology overcomes the limitations of conventional thermometers and thermocouples in organic solvent environments, enabling real-time, accurate internal temperature monitoring. The dual-function heating/cooling unit eliminates the need for traditional ice baths, facilitating fully automated temperature regulation throughout the experimental process while enhancing operational efficiency and measurement accuracy. Utilizing PID control algorithms, the system dynamically adjusts heating power according to the difference between target and actual temperatures, maintaining thermal stability and preventing temperature fluctuations, thereby improving reaction success rates and product purity. This automated design significantly reduces manual operation errors while improving experimental reproducibility and safety, offering novel approaches and technical support for digital education in organic chemistry experiments.