The Application of Last Observation Carried Forward Method for Missing Data Estimation in the Context of Industrial Wireless Sensor Networks

Thanks to advances in wireless communication technologies, the wireless sensor network (WSNs) have been attracting a lot of attention from academic communities and successfully applied to various domains. Along with developments of the Industry 4.0, the WSNs start to play a vital role in the construction of smart factories and realization of intelligent manufacturing. Although, the industrial WSNs (IWSNs) presents great quantity of advantages, there still have some drawbacks to overcome such as challenges of the quality of data for IWSNs. In order to resolve the data missing problems in the context of IWSNs, the Last Observation Carried Forward method is adopted to estimate the missing value and reconstruct the sensing dataset which takes into account the temporal characteristics of sensing data in IWSNs. Through experiments, this method is proved to be an easy and effective measurement for missing value imputation of the large multi-dimensional sensing data achieved by the IWSNs.