Target Tracking System Based on Wireless Sensor Networks

2010 ◽  
Author(s):  
Wei Fusheng ◽  
Zhou Shangli ◽  
Xiao Yong ◽  
Wu Shaocheng ◽  
Xu Bugong
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Tracking System ◽  
Wireless Sensor

Taxonomy of Cluster-Based Target Tracking System in Wireless Sensor Networks

2018 ◽  
Author(s):  
Ammar Odeh ◽  
Eman Abdelfattah ◽  
Mofleh Al diabate
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Tracking System ◽  
Cluster Formation ◽  
Wireless Sensor ◽  
Analysis Model ◽  
Massive Data Processing ◽  
The Internet Of Things ◽  
Big Data Technology

In the last decade, with the advancement of big data technology and the internet of things, wireless sensor networks (WSN) become fundamental for the success of different range of applications specially those demanding massive data processing. A target tracking system is a significant part of WSNs that has its own advantages and challenges. In this paper, the challenges of detecting and tracking a mobile device through cluster-based target tracking system in wireless sensor networks, are investigated. This paper investigates several tracking methods to introduce a novel cluster-based target tracking analysis model. In addition, some crucial factors of the cluster-based routing protocols are demonstrated, and a comparison among these different methods is conducted according to our taxonomy such as cluster formation, predicate/proactive, target speed, single or multi-object tracking, boundary problem, scalability, energy efficiency, and communication cost. Finally, a summary and conclusion are presented.

scholarly journals Analysis of Byzantine Attacks for Target Tracking in Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3436
Author(s):  
Yang ◽  
Xiong ◽  
Wang ◽  
Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Negative Impact ◽  
Tracking System ◽  
Wireless Sensor ◽  
Quantization Level ◽  
Importance Resampling ◽  
The Impact ◽  
Byzantine Attacks

Herein, the problem of target tracking in wireless sensor networks (WSNs) is investigated in the presence of Byzantine attacks. More specifically, we analyze the impact of Byzantine attacks on the performance of a tracking system. First, under the condition of jointly estimating the target state and the attack parameters, the posterior Cramer–Rao lower bound (PCRLB) is calculated. Then, from the perspective of attackers, we define the optimal Byzantine attack and theoretically find a way to achieve such an attack with minimal cost. When the attacked nodes are correctly identified by the fusion center (FC), we further define the suboptimal Byzantine attack and also find a way to realize such an attack. Finally, in order to alleviate the negative impact of attackers on the system performance, a modified sampling importance resampling (SIR) filter is proposed. Simulation results show that the tracking results of the modified SIR filter can be close to the true trajectory of the moving target. In addition, when the quantization level increases, both the security performance and the estimation performance of the tracking system are improved.

Taxonomy of Cluster-Based Target Tracking System in Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Ammar Odeh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Boundary Problem ◽  
Tracking System ◽  
Cluster Formation ◽  
Wireless Sensor ◽  
Analysis Model ◽  
Massive Data Processing ◽  
The Internet Of Things

Objective: In the last decade, with the advancement of big data technology and the internet of things, Wireless Sensor Networks (WSN) become fundamental for the success of a different range of applications especially those demanding massive data processing. Methods: This paper investigates several tracking methods to introduce a novel cluster-based target tracking analysis model. Results: Some crucial factors of the cluster-based routing protocols are demonstrated, and a comparison among these different methods is conducted according to our taxonomy such as cluster formation, predicate/proactive, target speed, single or multi-object tracking, boundary problem, scalability, energy efficiency, and communication cost. This can help the community of researchers by providing clear information for further study. Conclusion: The proposed paper compares the differences and similarities between the available approaches across different categories in terms of the Cluster construction, Clustering method, Object Speed, Number of Objects, Boundary problem, and scalability. Finally, we can recognize some open issues that have so far gained little publicity or remain unexplored yet.

A Target Tracking System Using Directional Nodes in Wireless Sensor Networks

2019 ◽  
Vol 13 (2) ◽  
pp. 1618-1627 ◽  
Author(s):  
Abhishek Tripathi ◽  
Hari Prabhat Gupta ◽  
Tanima Dutta ◽  
Durgesh Kumar ◽  
Satyabrat Jit ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Tracking System ◽  
Wireless Sensor

scholarly journals A Comparative Study of Target Tracking Approaches in Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Asmaa Ez-Zaidi ◽  
Said Rakrak
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Future Directions ◽  
Wide Range ◽  
Comprehensive Survey ◽  
The Subject ◽  
Intense Research

Wireless sensor networks have been the subject of intense research in recent years. Sensor nodes are used in wide range of applications such as security, military, and environmental monitoring. One of the most interesting applications in wireless sensor networks is target tracking, which mainly consists in detecting and monitoring the motion of mobile targets. In this paper, we present a comprehensive survey of target tracking approaches. We then analyze them according to several metrics. We also discuss some of the challenges that influence the performance of tracking schemes. In the end, we conduct detailed analysis and comparison between these algorithms and we conclude with some future directions.

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