Abstract: To collect and utilize dry and wet bulb temperature data in flue-curing barns during flue-curing, IoT (internet of things) technology was adopted to collect the data and Python program was used to establish algorithms for data cleaning, temperature and humidity curve identification, flue-curing stage identification and the process index analysis. The data from 13 493 flue-curing processes in tobacco producing areas in China from 2019 to 2021 were analyzed. The results showed that by adopting the IoT technology to collect the dry and wet bulb temperature data of flue-curing barns and combined with the developed algorithms, the flue-curing temperature and humidity curves of single flue-curing process in each barn could be automatically extracted, and the flue-curing process indexes such as time management, humidity management and abnormal temperature drop during the flue-curing process could be analyzed. The results indicated that the total flue-curing duration of 13 tobacco producing areas (cities and prefectures) was 139.1-188.5 h, in which the yellowing stage, color-fixing stage and stem-drying stage were 54.5-98.1 h, 48.9-69.7 h and 34.1-58.7 h respectively, accounting for 33.7%-53.2%, 27.5%-41.2% and 19.3%-31.7% of the total flue-curing duration. The wet bulb temperatures during the flue-curing process at the early yellowing stage, middle yellowing stage, late yellowing stage, early color-fixing stage, middle color-fixing stage, late color-fixing stage and late stem-drying stage were 35.7-36.9 ℃, 35.6-37.4 ℃, 34.5-36.9 ℃, 34.0-36.5 ℃, 34.3-37.1 ℃, 35.2-37.8 ℃ and 38.3-41.1 ℃. Based on the temperature and humidity data in a chronological order collected by IoT technology and combined with the algorithm identification and analysis, the performance of flue-curing processes could be analyzed rapidly and accurately.