Microcontroller-Based Kalman Filter Measurement of Ambient Temperature

Temperature measurement is critical in many aspects such as system safety, quality control, energy saving, and system performance. In industrial applications, temperature control is vital to prevent equipment from overheating and ensure worker safety. In energy management, energy savings are achieved by increasing the efficiency of heating, cooling, and air conditioning systems. Preventing overheating of electronic devices prolongs the performance and lifetime of these devices. In the health sector, temperature measurement is required for patient monitoring and correct operation of medical devices. In addition, in scientific research and the development of new technologies, temperature control is indispensable for the accuracy and reliability of experiments. In this context, temperature measurement is an essential component of maintaining operational excellence and safety standards in many industries. In this study, ambient temperature measurement is performed with an STM32F407VG microcontroller using an LM35 temperature sensor. The response of the LM35 temperature sensor is noisy due to light, radiation, high-frequency signals, etc. The noise from the sensor measurements was minimized by a Kalman filter design. These noises can be reduced by software or hardware filters. Hardware filters increase the system cost. In this study, a Kalman filter, which is one of the software filters, was used. A comparison between the Kalman filter and the alpha-beta filter has shown that the Kalman filter is more reliable and faster for dynamic systems. Experimental results show that the filter works very well.