Intelligent operators for localisation of dynamic smart dust networks

Graham A. Rollings, David W. Corne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)


Wireless Sensor Networks (WSN) of Smart dust motes are becoming increasingly effective in environmental monitoring applications. In some applications, data gathered via WSN are only useful when combined with individual mote positions and time-stamps; if the motes are not static, it is important to find methods for their 3D location estimation from available RSSI signal data. Usually termed 'Localisation', this problem is made more complex when the positions of the motes are subject to external forces. Here we extend our previous work on solving this problem with evolutionary algorithms; we experiment with 'geometric-awareness' operators that constrain the positions a WSN mote can occupy to those that have a better probability of maximally contributing to the chromosome fitness. A hybrid comprising the specialised and standard operators is also tested. We conclude that this research direction offers a viable basis for a heuristically directed evolutionary system capable of suitably accurate 3D localisation, thus increasing the possibilities for viable WSN applications. © 2008 IEEE.

Original languageEnglish
Title of host publicationProceedings - 8th International Conference on Hybrid Intelligent Systems, HIS 2008
Number of pages6
Publication statusPublished - 2008
Event8th International Conference on Hybrid Intelligent Systems - Barcelona, Spain
Duration: 10 Sept 200812 Sept 2008


Conference8th International Conference on Hybrid Intelligent Systems
Abbreviated titleHIS 2008


  • Environmental monitoring
  • Evolutionary algorithms
  • Geometric-awareness
  • Heuristically directed evolution
  • Location estimation
  • Smart dust


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