| Summary: | 碩士 === 朝陽科技大學 === 資訊工程系 === 107 === The purpose of this study is to construct an ammonia sensing transmission system based on the Kalman algorithm. In order to sense the target gas in the space, a large number of gas sensors are generally deployed in the sensing space, and a large amount of sensing data can improve the sensing accuracy and analyze the sensing characteristics. However, a large amount of sensing data will cause energy consumption and the congestion of the sensing network. Therefore, this study attempts to use the Kalman filter to filter the signal so that the signal is relatively flat. This is beneficial to the early construction of the data.
The wireless ammonia sensing system constructed based on the Kalman filter algorithm in this study combine the concept of slope and sensitivity to find the turning point during the sensing period. The data of the original data processed by the Kalman filter is compared with the original data, and then the error rate is used as the classification. Performing the above method can suppress noise and reduce the amount of data transmitted, thereby reducing the energy consumption during transmission. The Lagrange interpolation method is used to restore the reduced data. From the simulation results, the algorithm for reducing data can remove the data more than 97%. Use the Lagrange interpolation method to make up the removed data. By performing this method and comparing the original data, we can find that the average error is less than 0.28%.
In addition, this study designed the ammonia sensing monitoring system for web pages and mobile APPs. Users are no longer limited to monitoring in front of computers, and can use mobile APP to remotely monitor. When a hazard is detected, an immediate alarm can be issued and the leaked gas can be turned off for safety.
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