DDDAMS-Based Border Surveillance and Crowd Control via Aerostats, UAVs, and Ground Sensors

Seunghan Lee, Sara Minaeian, Yifei Yuan, Jian Liu, Young-Jun Son

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

2 Scopus citations

Abstract

The primary goal of this research is to explore algorithmic approaches to build a robust, multi-scale, affordable, and effective border surveillance strategies for tracking aerial and ground targets (e.g. drug-smuggling UAVs) via various types of sensors in three layers. To this end, we propose a comprehensive planning and control framework based on dynamic-data-driven, adaptive multi-scale simulation (DDDAMS). Dynamic data is incorporated into the simulation process to improve its validity, at the same time simulation steers the measurement process to improve data usability. In addition, an appropriate level of simulation fidelity is selected based on the time constraints to evaluate alternative control strategies using simulation. In this research, a DDDAMS framework that was previously developed for multiple UAVs will be further extended to address effective surveillance problems and crowd control in a much boarder border area via multiple sensors in a 3-levels hierarchy including aerostats, UAVs and ground sensors. Finally, preliminary data analysis is provided for two major sensors (i.e. vision and seismic data) used in the considered surveillance application.

Original languageEnglish (US)
Title of host publicationProceedings - 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages348-351
Number of pages4
ISBN (Electronic)9781509065585
DOIs
StatePublished - Oct 9 2017
Event2nd IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017 - Tucson, United States
Duration: Sep 18 2017Sep 22 2017

Other

Other2nd IEEE International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017
CountryUnited States
CityTucson
Period9/18/179/22/17

Keywords

  • Border Surveillance
  • DDDAS
  • Multi-level surveillance
  • Sensors
  • UAVs

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Computational Mechanics

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    Lee, S., Minaeian, S., Yuan, Y., Liu, J., & Son, Y-J. (2017). DDDAMS-Based Border Surveillance and Crowd Control via Aerostats, UAVs, and Ground Sensors. In Proceedings - 2017 IEEE 2nd International Workshops on Foundations and Applications of Self* Systems, FAS*W 2017 (pp. 348-351). [8064147] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FAS-W.2017.171