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access icon openaccess Research on optimisation processing of spatiotemporal correlation temperature and humidity data based on wireless sensor networks in cigarette factory

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 18/10/2018, Accepted 20/02/2019, Revised 18/02/2019, Published 25/03/2019

The tobacco leaves have higher requirements on the environment during production and storage, especially for the temperature and humidity. In order to improve the quality of tobacco leaves, it is necessary to accurately monitor the temperature and humidity and optimise the parameters involved in the control. Based on the temperature and humidity monitoring system of cigarette factory, the authors optimised the temperature and humidity data obtained by wireless sensors. The data quality evaluation indicators were designed, and the Dixon criterion was used to eliminate gross errors in individual data instance. The abnormal data detection mechanism is designed to eliminate the fault data in multiple data instances by the similarity criteria among neighbour nodes in the area. In order to solve the problem of excessive computation caused by node explosion, extended rules of healthy node judgment were designed. Through the actual operation of the system for >6 months, the algorithm maintains good fault detection capabilities for different fault models and can provide support for temperature and humidity data processing of wireless sensor networks (WSNs).

Inspec keywords: tobacco industry; fault diagnosis; humidity measurement; temperature measurement; wireless sensor networks; optimisation

Other keywords: abnormal data detection mechanism; tobacco leaves quality; similarity criteria; optimisation processing; data quality evaluation indicators; time 6.0 month; Dixon criterion; healthy node judgment; gross error elimination; node explosion; fault data; fault models; spatiotemporal correlation temperature; humidity monitoring system; multiple data instances; fault detection capabilities; cigarette factory; humidity data processing; temperature monitoring system; wireless sensor networks; neighbour nodes

Subjects: Wireless sensor networks; Humidity measurement; Other manufacturing industries; Sensing devices and transducers; Optimisation; Optimisation techniques; Thermal variables measurement

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