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Published in:
2021 | OriginalPaper | Chapter
Assumption of Missing Processing of Sensor Acquisition Data Based on Multiple Interpolation
Authors : Zhuo Li, Yufan Liu, Helong Yu, You Tang
Published in: Big Data Analytics for Cyber-Physical System in Smart City
Publisher: Springer Singapore
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Abstract
With the rapid development of the Internet of Things technology, the use of sensors to collect data has become a more popular method, but because of the different environment of the sensor, the working state of the sensor must be relatively high, such as in greenhouses such as high temperatures In a high-humidity environment, whether the sensor can work normally; in a continuous working condition of 7 * 24 h, whether the data collected by the sensor can be trusted is a question that must be considered. In the real environment, the environment is complex and changeable. The data collected by the sensor may be inaccurate. In more extreme cases, the sensor may not collect data, that is, there is missing data. In order to deal with the missing data, this article takes a greenhouse as an example, and compares the four dimensions of light intensity, carbon dioxide concentration, temperature, and humidity, and uses multiple interpolation methods to fill in missing sensor data.