Barrier Coverage for 3D Camera Sensor Networks

Si, Pengju; Wu, Chengdong; Zhang, Yunzhou; Jia, Zhenhong; Ji, Peng; Chen, Hao

doi:10.3390/s17081771

Cited by 20 publications

(16 citation statements)

References 41 publications

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“…Thus, the work in [ 16 , 17 , 18 ] assumed the probabilistic sensing model. Moreover, state-of-the-art research work considers more practical issues such as the utilization of the three-dimensional (3D) sensing model in camera sensor networks [ 19 ] and the joint probability model in the compound event barrier coverage problem [ 20 ]. However, we adopt the Boolean disc sensing model in our research since we are the first to study the crossed barrier coverage problem.…”

Section: Related Workmentioning

confidence: 99%

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network

Han

Yang

Zhang

2018

Sensors

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Barrier coverage has been widely used to detect intrusions in wireless sensor networks (WSNs). It can fulfill the monitoring task while extending the lifetime of the network. Though barrier coverage in WSNs has been intensively studied in recent years, previous research failed to consider the problem of intrusion in transversal directions. If an intruder knows the deployment configuration of sensor nodes, then there is a high probability that it may traverse the whole target region from particular directions, without being detected. In this paper, we introduce the concept of crossed barrier coverage that can overcome this defect. We prove that the problem of finding the maximum number of crossed barriers is NP-hard and integer linear programming (ILP) is used to formulate the optimization problem. The branch-and-bound algorithm is adopted to determine the maximum number of crossed barriers. In addition, we also propose a multi-round shortest path algorithm (MSPA) to solve the optimization problem, which works heuristically to guarantee efficiency while maintaining near-optimal solutions. Several conventional algorithms for finding the maximum number of disjoint strong barriers are also modified to solve the crossed barrier problem and for the purpose of comparison. Extensive simulation studies demonstrate the effectiveness of MSPA.

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Section: Related Workmentioning

confidence: 99%

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network

Han

Yang

Zhang

2018

Sensors

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“…Wutthigrai Boonsuk [16] implemented a stereo vision system for industrial robotics and concluded the following: shorter baseline distances performs better at shorter distances to the target, but at longer distances, wide baselines are better. Si et al [17] used camera sensor networks to detect intrusions passing through a barrier area. They implemented multiple parallel cameras in order to guarantee a maximum coverage for the monitored barrier.…”

Section: Disparity Maps In Wireless Multimedia Sensor Networkmentioning

confidence: 99%

Wireless multimedia sensor network deployment for disparity map calculation

Tannoury

Darazi

Makhoul

et al. 2018

2018 IEEE Middle East and North Africa Communications Conference (MENACOMM)

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The use of Wireless Multimedia Sensor Networks (WMSNs) has been increased in the recent decade in several fields. One of the main advantages of WMSNs is activity monitoring, where 2D images and videos have been used traditionally for surveillance and detection so far. However, a lot of interest is paid to depth information that is not normally available while using 2D images. In our previous work, the use of disparity information in WMSNs has been studied. In this paper, our contribution consists of evaluating the Sensor deployment for efficient disparity calculation for indoor and outdoor purposes. The simulation results show that while considering images from adjacent sensors, the disparity map is successfully calculated. The quality of the disparity is evaluated using structural similarity metric between one reference image captured by one sensor and the calculated disparity map.

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“…With the development of embedded systems and communication technology, wireless multimedia sensor networks (WMSN) have assumed a prominent scientific position [1,2]. Accordingly, WMSN constitute a winning solution with their information acquisition method and processing technology, and allow the acquisition of complete information in the monitoring area, especially video data [3]. They have been extensively used in different applications, such as military affairs, public security, environmental monitoring/forecasting, home automation, and in intelligent transportation [4,5,6].…”

Section: Introductionmentioning

confidence: 99%

“…Owing to the importance of WMSN, researchers have conducted extensive studies in this area [7,8]. Most of the existing studies have concentrated on localization [9], barrier coverage [3], data fusion [10], and sensor deployment [11]. Among these studies, the sensor network deployment problem guarantees the coverage of the monitoring area corresponding to the sensors, and provides the foundation of all the upper-layer applications.…”

Section: Introductionmentioning

confidence: 99%

A 3D Coverage Algorithm Based on Complex Surfaces for UAVs in Wireless Multimedia Sensor Networks

Jia

Yang³

et al. 2019

Sensors

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Following the development of wireless multimedia sensor networks (WMSN), the coverage of the sensors in the network constitutes one of the key technologies that have a significant influence on the monitoring ability, quality of service, and network lifetime. The application environment of WMSN is always a complex surface, such as a hilly surface, that would likely cause monitoring shadowing problems. In this study, a new coverage-enhancing algorithm is presented to achieve an optimal coverage ratio of WMSN based on three-dimensional (3D) complex surfaces. By aiming at the complex surface, the use of a 3D sensing model, including a sensor monitoring model and a surface map calculation algorithm, is proposed to calculate the WMSN coverage information in an accurate manner. The coverage base map allowed the efficient estimation of the degree of monitoring occlusion efficiently and improved the system’s accuracy. To meet the requests of complex 3D surface monitoring tasks for multiple sensors, we propose a modified cuckoo search algorithm that considers the features of the WMSN coverage problem and combines the survival of the fittest, dynamic discovery probability, and the self-adaptation strategy of rotation. The evaluation outcomes demonstrate that the proposed algorithm can describe the 3D covering field but also improve both the coverage quality and efficiency of the WMSN on a complex surface.

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Barrier Coverage for 3D Camera Sensor Networks

Cited by 20 publications

References 41 publications

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network

Wireless multimedia sensor network deployment for disparity map calculation

A 3D Coverage Algorithm Based on Complex Surfaces for UAVs in Wireless Multimedia Sensor Networks

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