Increasing agricultural productivity is a global concern as food security is expected at the risk in the near future. Lots of information technology based studies have shown positive effects in analysing and streamlining the agricultural work. However due to frequent data shortage, it is difficult to facilitate precision agriculture. Then an easy deploying, preprocess-integrated data acquisition system may help to solve these problem. This paper presents a system that generates various temporal data streams and refines them automatically. The system has a server and one or more station. The station is dedicated to a plant and collecting a heterogeneous data periodically. The number of station is easily extendable to gather more crop’s information. For effective data collection, all sensors have the same sampling period, 1 min. This sampling period is based on the daylight and its mathematical foundation is presented too. Data preprocess is conducted with low-pass filter and resampler. A method to find an optimal filter based on root-mean-square-error is proposed and analysed.
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