Adaptive Video Streaming in Hybrid Landslide Detection System with D-S Theory

Zhi Liu, Kenji Kanai, Masaru Takeuchi, Toshitaka Tsuda, Hiroshi Watanabe

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

Abstract

Disaster detection is an important research topic and draws great attentions from both industry and academia. In this paper, we study the hybrid landslide detection system, which utilizes the video surveillance camera and multiple kinds of sensors and can detect the landslide automatically. Edge processing is adopted in this hybrid system to fuse the sensor data based on the Dempster-Shafer (D-S) theory, i.e. utilizing multiple sensors' information to calculate the possibility of the landslide. Edge processing can make faster decisions than the control center, the results of the edge processing are then used to schedule the sensor's transmission frequency and video transmission under the network constraints in this system. The simulation results show that the proposed scheme outperforms the competing schemes in typical network scenarios.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509065172
DOIs
Publication statusPublished - 2017 Jun 12
Event2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017 - Hong Kong, China
Duration: 2017 May 292017 May 31

Other

Other2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017
CountryChina
CityHong Kong
Period17/5/2917/5/31

Keywords

  • Dempster-Shafer (DS)
  • disaster
  • landslide
  • video streaming
  • WSN

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

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  • Cite this

    Liu, Z., Kanai, K., Takeuchi, M., Tsuda, T., & Watanabe, H. (2017). Adaptive Video Streaming in Hybrid Landslide Detection System with D-S Theory. In 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017 [7946984] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMARTCOMP.2017.7946984