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

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

doi:10.1109/SMARTCOMP.2017.7946984

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

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

Waseda Research Institute for Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

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 language	English
Title of host publication	2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781509065172
DOIs	https://doi.org/10.1109/SMARTCOMP.2017.7946984
Publication status	Published - 2017 Jun 12
Event	2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017 - Hong Kong, China Duration: 2017 May 29 → 2017 May 31

Other

Other	2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017
Country/Territory	China
City	Hong Kong
Period	17/5/29 → 17/5/31

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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10.1109/SMARTCOMP.2017.7946984

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Adaptive Video Streaming in Hybrid Landslide Detection System with D-S Theory. / Liu, Zhi; Kanai, Kenji; Takeuchi, Masaru; Tsuda, Toshitaka; Watanabe, Hiroshi.

2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017. Institute of Electrical and Electronics Engineers Inc., 2017. 7946984.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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., 2017 IEEE International Conference on Smart Computing, SMARTCOMP 2017, Hong Kong, China, 17/5/29. https://doi.org/10.1109/SMARTCOMP.2017.7946984

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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.",

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N2 - 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.

AB - 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.

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

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Keywords

ASJC Scopus subject areas

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