Optimization of Temperature Sensor Selection for Incubators: Real-Time Accuracy Analysis of DHT22, LM35, and DS18B20 in Controlled Environment Simulations - siswoyo, agus (Internet of Things and Artificial Intelligence Journal, 2025)
Temperature measurement accuracy is a critical factor in incubator systems, especially for medical and biological applications that require high precision. This study aims to analyze the performance of three popular temperature sensors (DHT22, LM35, and DS18B20) in the context of an incubator through controlled environment simulations, to determine the optimal sensor based on real-time accuracy, response time, and stability. The experimental method was carried out by replicating the operational conditions of the incubator using a climate chamber set at a temperature range of 30–40°C and a humidity of 60–80% RH. The sensor accuracy data was compared with a medical-grade reference thermometer (Fluke 1551A), while the response time was measured through a simulation of dynamic temperature changes (±5°C). The results showed that the DS18B20 recorded the highest accuracy with an average deviation of ±0.3°C and a response time of 2–3 seconds, supported by an interference-resistant 1-Wire digital interface. The LM35 exhibits good linearity (±0.5°C) but is susceptible to electrical noise without shielding, while the DHT22 has lower accuracy (±0.8°C) due to the influence of internal humidity on the measurement system. This study also reveals the need for regular calibration of the LM35 and a closed enclosure design for the DHT22 to minimize environmental errors. The study's conclusions recommend the DS18B20 as the optimal choice for high-precision medical incubators, with the inclusion of digital filters for signal optimization. These findings provide practical guidance for developers in selecting temperature sensors according to incubator design needs, whether for healthcare, biotechnology, or precision agriculture applications.