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Advanced Sensor Fusion for Railway Security - A Hierarchical Graph-Based Approach

Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review

Abstract

Ensuring effective security surveillance in the railway sector presents a number of significant challenges, largely due to the extensive and dispersed nature of railway infrastructure. To effectively address threats such as vandalism, trespassing and sabotage, it is essential to implement continuous and comprehensive monitoring systems. Despite recent advances in technology, the issue of false alarms and information overload remains a significant challenge, undermining the efficiency of security operations. To overcome these challenges, recent studies have investigated the use of multi-modal fusion systems, which have proven effective in reducing false alarms. This paper introduces a Hierarchical Fusion Graph (HFG) as a generalised approach for interpreting a fusion system as a directed acyclic graph (DAG), enhancing the scalability and flexibility of sensor data fusion.
Original languageEnglish
Title of host publication2024 Sensor Data Fusion: Trends, Solutions, Applications, SDF 2024
Pages1-7
Number of pages7
ISBN (Electronic)979-8-3315-2744-0
DOIs
Publication statusPublished - 5 Feb 2025
Event2024 Sensor Data Fusion: Trends, Solutions, Applications (SDF) - Bonn, Bonn, Germany
Duration: 25 Nov 202427 Nov 2024

Publication series

Name2024 Sensor Data Fusion: Trends, Solutions, Applications, SDF 2024

Conference

Conference2024 Sensor Data Fusion: Trends, Solutions, Applications (SDF)
Country/TerritoryGermany
CityBonn
Period25/11/2427/11/24

Research Field

  • Responsive Sensing & Analytics

Keywords

  • Sensor data fusion
  • critical infrastructure protection
  • directed acyclic graph
  • fusion systems

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