Original Article

Neural Computing & Applications

, Volume 14, Issue 4, pp 273-281

A Review of data fusion models and architectures: towards engineering guidelines

  • Jaime EstebanAffiliated withSchool of Mechanical, Aerospace and Civil Engineering, The University of Manchester
  • , Andrew StarrAffiliated withSchool of Mechanical, Aerospace and Civil Engineering, The University of Manchester
  • , Robert WillettsAffiliated withSchool of Mechanical, Aerospace and Civil Engineering, The University of Manchester
  • , Paul HannahAffiliated withSchool of Mechanical, Aerospace and Civil Engineering, The University of Manchester
  • , Peter Bryanston-CrossAffiliated withSchool of Engineering, University of Warwick

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Abstract

This paper reviews the potential benefits that can be obtained by the implementation of data fusion in a multi-sensor environment. A thorough review of the commonly used data fusion frameworks is presented together with important factors that need to be considered during the development of an effective data fusion problem-solving strategy. A system-based approach is defined for the application of data fusion systems within engineering. Structured guidelines for users are proposed.

Keywords

Data fusion Frameworks Intelligent systems Engineering guidelines