Presentation Information
[7p-P04-21]Wind speed prediction by machine learning for printed wind speed sensor using polymer semiconductors
〇Kanta Toda1, Seiga Shinmura1, Hiroyuki Matsui1 (1.ROEL, Yamagata Univ.)
Keywords:
machine learning,organic semiconductor
Wind sensors are expected to have a wide range of applications, including IoT and environmental monitoring. However, conventional fabrication methods that rely on vacuum deposition processes face challenges in achieving low cost and mass production. In our laboratory, we previously developed a temperature sensor with a high temperature coefficient by chemically doping the polymer semiconductor poly-TPD with F4TCNQ using a solution-based method. In this study, we applied this technology to develop a printed wind sensor and investigated a method for estimating wind velocity vectors by combining the sensor with machine learning.