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BLE beacons for sample position estimation in a life science automation laboratory

Transportation Safety and Environment 2024年第3期6卷 111-123页

作者： Haiping Wu Steffen Junginger Thomas Roddelkopf Hui Liu Kerstin Thurow Institute of Artificial Intelligence&Robotics(IAIR) Key Laboratory of Traffic Safety on Track of Ministry of EducationSchool of Traffic and Transportation EngineeringCentral South UniversityChangsha 410075HunanChina Institute of Automation(IAT) University of Rostock18119 RostockGermany Center of Life Science Automation(celisca) University of Rostock18119 RostockGermany

estimation of the sample position is essential for working process monitoring and management in the life science automation lab*** low-energy(BLE)beacons have the advantages of low price,small size and low energy consumption,which make them a promising solution for sample position estimation in the automated *** fingerprinting models have been proposed to achieve indoor localization with the received signal strength(RSS)***,most of the research depends on intensive beacon *** estimation,which depends entirely on one beacon,is more suitable for sample position estimation in large automated *** complexity of the life science automation laboratory environment brings challenges to the traditional path loss model(PLM),which is a widely used radio wave propagation model-based proximity estimation *** this paper,BLE sensing devices for sample position estimation are *** BLE beacon-based proximity estimation is discussed in the framework of machine learning,in which the support vector regression(SVR)is utilized to model the nonlinear relationship between the RSS data and distance,and the Kalman filter is utilized to decrease the RSS data *** experimental results over different environments indicate that the SVR outperforms the PLM significantly,and provides 1 m absolute errors for more than 95%of the testing *** Kalman filter brings benefits to stable distance *** from proximity-based sample position estimation,the proposed framework turned out to be effective in position estimation between parallel workbenches and position estimation on an automated workstation.

关键词： BLE beacon position estimation proximity estimation received signal strength(RSS) support vector regression(SVR) life science automation laboratory

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