Time-selective data fusion for in-network processing in ad hoc wireless sensor networks. (November 2018)

• Record Type: Journal Article
• Authors: Kaugerand, Jaanus; Ehala, Johannes; Mõtus, Leo; Preden, Jürgo-Sören
• Is Part Of: International journal of distributed sensor networks. Volume 14:Number 11(2018)
• Publication Date: 2018-11
• Subjects: Time-selective data fusion -- in-network data processing -- data validity -- data alignment -- data simultaneity -- wireless ad hoc sensor networks -- situation awareness -- middleware; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147718811302
• Languages: English
• ISSNs: 1550-1329

Abstract

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.