Optical sensor networks for high-speed railway applications (Invited Paper)

Survivable Deployments of Optical Sensor Networks against Multiple Failures and Disasters: A Survey

Sensors ◽

10.3390/s19214790 ◽

2019 ◽

Vol 19 (21) ◽

pp. 4790 ◽

Cited By ~ 2

Author(s):

Yongjun Zhang ◽

Jingjie Xin

Keyword(s):

Sensor Networks ◽

Optical Communication ◽

Optical Sensor ◽

Data Transmission ◽

High Speed ◽

Optical Sensing ◽

Self Healing ◽

Multiple Failures ◽

Sensing Data ◽

Potential Development

Optical sensing that integrates communication and sensing functions is playing a more and more important role in both military and civil applications. Incorporating optical sensing and optical communication, optical sensor networks (OSNs) that undertake the task of high-speed and large-capacity applications and sensing data transmissions have become an important communication infrastructure. However, multiple failures and disasters in OSNs can cause serious sensing provisioning problems. To ensure uninterrupted sensing data transmission, survivability has always been an important research emphasis. This paper focuses on the survivable deployment of OSNs against multiple failures and disasters. We first review and evaluate the existing survivability technologies developed for or applied to OSNs, such as fiber bus protection, self-healing architecture, and 1 + 1 protection. We then elaborate on the disaster-resilient survivability requirement of OSNs. Moreover, we propose a new k-node (edge) sensing connectivity concept, which ensures the connectivity between sensing data and users. Based on k-node (edge) sensing connectivity, the disaster-resilient survivability technologies are developed. The key technologies necessary to implement k-node (edge) sensing connectivity are also elaborated. Recently, artificial intelligence (AI) has developed rapidly. It can be used to improve the survivability of OSNs. This paper details potential development directions of survivability technologies of optical sensing in OSNs employing AI.

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A Passenger Flow Risk Forecasting Algorithm for High-Speed Railway Transport Hub Based on Surveillance Sensor Networks

Journal of Sensors ◽

10.1155/2016/5647909 ◽

2016 ◽

Vol 2016 ◽

pp. 1-6

Author(s):

Zhengyu Xie ◽

Yong Qin

Keyword(s):

Sensor Networks ◽

Spatial Correlation ◽

High Speed ◽

Safety Management ◽

Computational Results ◽

Railway Transport ◽

High Speed Railway ◽

Passenger Flow ◽

Risk Forecasting

Passenger flow risk forecasting is a vital task for safety management in high-speed railway transport hub. In this paper, we considered the passenger flow risk forecasting problem in high-speed railway transport hub. Based on the surveillance sensor networks, a passenger flow risk forecasting algorithm was developed based on spatial correlation. Computational results showed that the proposed forecasting approach was effective and significant for the high-speed railway transport hub.

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Sensor Networks Hierarchical Optimization Model for Security Monitoring in High-Speed Railway Transport Hub

Journal of Sensors ◽

10.1155/2015/951242 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9 ◽

Cited By ~ 1

Author(s):

Zhengyu Xie ◽

Yong Qin

Keyword(s):

Sensor Networks ◽

Optimization Model ◽

High Speed ◽

Optimization Problem ◽

Optimization Method ◽

Hierarchical Optimization ◽

Railway Transport ◽

High Speed Railway ◽

Security Monitoring

We consider the sensor networks hierarchical optimization problem in high-speed railway transport hub (HRTH). The sensor networks are optimized from three hierarchies which are key area sensors optimization, passenger line sensors optimization, and whole area sensors optimization. Case study on a specific HRTH in China showed that the hierarchical optimization method is effective to optimize the sensor networks for security monitoring in HRTH.

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