Time-selective data fusion for in-network processing in ad hoc wireless sensor networks

作     者：Kaugerand, Jaanus Ehala, Johannes Motus, Leo Preden, Jurgo-Soren 

作者机构：Tallinn Univ Technol Res Lab Proact Technol Ehitajate Tee 5 EE-19086 Tallinn Estonia Thinnect Inc Sunnyvale CA USA 

出 版 物：《INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS》 (分布式传感网络国际杂志)

年 卷 期：2018年第14卷第11期

页      面：1-1页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：European Regional Development Fund Estonian IT Academy program project SMENETE (Smart Environment Networking Technologies) 

主　　题：Time-selective data fusion in-network data processing data validity data alignment data simultaneity wireless ad hoc sensor networks situation awareness middleware 

摘      要：This article introduces a time-selective strategy for enhancing temporal consistency of input data for multi-sensor data fusion for in-network data processing in ad hoc wireless sensor networks. Detecting and handling complex time-variable (real-time) situations require methodical consideration of temporal aspects, especially in ad hoc wireless sensor network with distributed asynchronous and autonomous nodes. For example, assigning processing intervals of network nodes, defining validity and simultaneity requirements for data items, determining the size of memory required for buffering the data streams produced by ad hoc nodes and other relevant aspects. The data streams produced periodically and sometimes intermittently by sensor nodes arrive to the fusion nodes with variable delays, which results in sporadic temporal order of inputs. Using data from individual nodes in the order of arrival (i.e. freshest data first) does not, in all cases, yield the optimal results in terms of data temporal consistency and fusion accuracy. We propose time-selective data fusion strategy, which combines temporal alignment, temporal constraints and a method for computing delay of sensor readings, to allow fusion node to select the temporally compatible data from received streams. A real-world experiment (moving vehicles in urban environment) for validation of the strategy demonstrates significant improvement of the accuracy of fusion results.