scholarly journals Tracking and Localization based on Multi-angle Vision for Underwater Target

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1871
Author(s):  
Jun Liu ◽  
Shenghua Gong ◽  
Wenxue Guan ◽  
Benyuan Li ◽  
Haobo Li ◽  
...  
Keyword(s):  
Image Enhancement ◽  
Network Architecture ◽  
Tracking System ◽  
Saliency Detection ◽  
Target Position ◽  
Video Stream ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Dynamic Target ◽  
Underwater Target

With the cost reduction of underwater sensor network nodes and the increasing demand for underwater detection and monitoring, near-land areas, shallow water areas, lakes and rivers have gradually tended to densely arranged sensor nodes. In order to achieve real-time monitoring, most nodes now have visual sensors instead of acoustic sensors to collect and analyze optical images, mainly because cameras might be more advantageous when it comes to dense underwater sensor networks. In this article, image enhancement, saliency detection, calibration and refraction model calculation are performed on the video streams collected by multiple optical cameras to obtain the track of the dynamic target. This study not only innovatively combines the application of AOD-Net’s (all-in-one network) image defogging algorithm with underwater image enhancement, but also refers to the BASNet (Boundary-Aware Salient network) network architecture, introducing frame difference results in the input to reduce the interference of static targets. Based on the aforementioned technologies, this paper designs a dynamic target tracking system centered on video stream processing in dense underwater networks. As part of the process, most nodes carried underwater cameras. When the dynamic target could be captured by at least two nodes in the network at the same time, the target position could then be calculated and tracked.

scholarly journals Perturbation Propagation Models for Underwater Sensor Localisation using Semidefinite Programming

2021 ◽  
Vol 71 (6) ◽  
pp. 807-815
Author(s):  
Prateek . ◽  
Rajeev Arya
Keyword(s):  
Semidefinite Programming ◽  
Real Time ◽  
Forward Direction ◽  
Sensor Nodes ◽  
Rectilinear Motion ◽  
Underwater Sensor Networks ◽  
Propagation Models ◽  
Target Localisation ◽  
Novel Target ◽  
Underwater Target

Real time Underwater sensor networks (UWSNs) suffer from localisation issues due to a dearth of incorporation of different geometric scenarios in UWSN scenarios. To address these issues, this paper visualises three specific scenarios of perturbation. First, small sized and large numbered particles of perturbance moving in a tangential motion to the sensor nodes; second, a single numbered and large-sized particle moving in a rectilinear motion by displacing the sensor nodes into sideward and forward direction, and third, a radially outward propagating perturbance to observe the influenced sensor nodes as the perturbance moves outwards. A novel target localisation and tracking is facilitated by including marine vehicle navigation as a source of perturbation. Using semidefinite programming, the proposed perturbation models minimise localisation errors, thereby enhancing physical security of underwater sensor nodes. By leveraging the spin, cleaving motion and radial cast-away behaviour of underwater sensor nodes, the results confirm that the proposed propagation models can be conveniently applied to real time target detection and estimation of underwater target nodes.

Security based on Received Signal Strength in Localization for Underwater Sensor Networks

2016 ◽  
Vol 1 (2) ◽  
pp. 1-7
Author(s):  
Karamjeet Kaur ◽  
Gianetan Singh Sekhon
Keyword(s):  
Sensor Networks ◽  
Threshold Value ◽  
Critical Issue ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Research Subjects ◽  
Malicious Nodes ◽  
Intermediate Node ◽  
End To End Delay ◽  
End To End

Underwater sensor networks are envisioned to enable a broad category of underwater applications such as pollution tracking, offshore exploration, and oil spilling. Such applications require precise location information as otherwise the sensed data might be meaningless. On the other hand, security critical issue as underwater sensor networks are typically deployed in harsh environments. Localization is one of the latest research subjects in UWSNs since many useful applying UWSNs, e.g., event detecting. Now day’s large number of localization methods arrived for UWSNs. However, few of them take place stability or security criteria. In purposed work taking up localization in underwater such that various wireless sensor nodes get localize to each other. RSS based localization technique used remove malicious nodes from the communication intermediate node list based on RSS threshold value. Purposed algorithm improves more throughput and less end to end delay without degrading energy dissipation at each node. The simulation is conducted in MATLAB and it suggests optimal result as comparison of end to end delay with and without malicious node.

Wearable energy-efficient fitness tracking system for sports person health monitoring application

2021 ◽  
pp. 1-13
Author(s):  
Dan Xie ◽  
Ming Zhang ◽  
Priyan Malarvizhi Kumar ◽  
Bala Anand Muthu
Keyword(s):  
Health Monitoring ◽  
Energy Efficient ◽  
Tracking System ◽  
Path Loss ◽  
Integrated Approach ◽  
Smartphone Application ◽  
Sensor Nodes ◽  
Engineering Research ◽  
Fitness Tracking ◽  
Monitoring Application

The high potential of wearable physiological sensors in regenerative medicine and continuous monitoring of human health is currently of great interest. In measuring in real-time and non-invasively highly heterogeneous constituents, have a great deal of work and therefore been pushed into creating several sports monitoring sensors. The advanced engineering research and technology lead to the design of a wearable energy-efficient fitness tracking (WE2FT) system for sports person health monitoring application. Instantaneous accelerations are measured against pulses, and specific walking motions can be tracked by this system using a deep learning-based integrated approach of an intelligent algorithm for gait phase detection for the proposed system (WE2FT). The algorithm’s effects are addressed, and the performance has been evaluated. In this study, the algorithm uses a smartphone application to track steps using the Internet of Things (IoT) technology. For this initiative, the central node’s optimal location is measured with the antenna reflectance coefficient and CM3A path loss model (IEEE 802.15.6) among the sensor nodes for energy-efficient communication. The simulation experiment results in the highest performance in terms of energy efficiency and path loss.

Deployment Strategy in Distributed Underwater Sensor Networks

2014 ◽  
Vol 602-605 ◽  
pp. 3643-3647
Author(s):  
Li Yan Liu ◽  
Rong Fu ◽  
Yi He ◽  
Ying Qian Zhang
Keyword(s):  
Network Performance ◽  
Heuristic Method ◽  
Grid Method ◽  
Sensor Nodes ◽  
Triangular Grid ◽  
Underwater Sensor Networks ◽  
Network Coverage ◽  
Coverage Ratio ◽  
Initial Node ◽  
Deployment Strategy

Distributed underwater sensor network coverage is divided into two main categories: deterministic coverage and stochastic coverage. A strategy is put forward to deploy determinate area by using a triangular-grid method. When a coverage ratio is known, the distance between nodes can be adjusted to meet the coverage ratio in the monitored area, and the least number of sensor nodes can be calculated. Also a heuristic method is proposed for stochastic area deployment strategy. It is under the premise that the initial node location randomly deployed is given, using Voronoi diagram, the not easiest monitored path is searched, and the network coverage performance is improved by configuring the new nodes in the path. Finally it is proved that network performance is more improved by the simulation experiments, when one to four nodes are configured in the easiest breach path.

scholarly journals Bayesian Compressive Sensing Based Optimized Node Selection Scheme in Underwater Sensor Networks

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2568 ◽  
Author(s):  
Ruisong Wang ◽  
Gongliang Liu ◽  
Wenjing Kang ◽  
Bo Li ◽  
Ruofei Ma ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Compressed Sensing ◽  
Bayesian Estimation ◽  
Sensor Node ◽  
Optimization Problem ◽  
Sensor Nodes ◽  
Underwater Sensor Networks ◽  
Node Selection ◽  
Selection Scheme ◽  
Error Covariance

Information acquisition in underwater sensor networks is usually limited by energy and bandwidth. Fortunately, the received signal can be represented sparsely on some basis. Therefore, a compressed sensing method can be used to collect the information by selecting a subset of the total sensor nodes. The conventional compressed sensing scheme is to select some sensor nodes randomly. The network lifetime and the correlation of sensor nodes are not considered. Therefore, it is significant to adjust the sensor node selection scheme according to these factors for the superior performance. In this paper, an optimized sensor node selection scheme is given based on Bayesian estimation theory. The advantage of Bayesian estimation is to give the closed-form expression of posterior density function and error covariance matrix. The proposed optimization problem first aims at minimizing the mean square error (MSE) of Bayesian estimation based on a given error covariance matrix. Then, the non-convex optimization problem is transformed as a convex semidefinite programming problem by relaxing the constraints. Finally, the residual energy of each sensor node is taken into account as a constraint in the optimization problem. Simulation results demonstrate that the proposed scheme has better performance than a conventional compressed sensing scheme.

Research on Underwater Target Tracking Based on Contour Detection

2011 ◽  
Vol 317-319 ◽  
pp. 890-896
Author(s):  
Ming Jun Zhang ◽  
Yuan Yuan Wan ◽  
Zhen Zhong Chu
Keyword(s):  
Prediction Model ◽  
Target Tracking ◽  
Tracking System ◽  
Contour Detection ◽  
Motion Prediction ◽  
Moving Target ◽  
Contour Extraction ◽  
Tracking Accuracy ◽  
Tracking Method ◽  
Underwater Target

The traditional centroid tracking method over-relies on the accuracy of segment, which easily lead to loss of underwater moving target. This paper presents an object tracking method based on circular contour extraction, combining region feature and contour feature. Through the correction to circle features, the problem of multiple solutions causing by Hough transform circle detection is avoided. A new motion prediction model is constructed to make up the deficiency that three-order motion prediction model has disadvantage of high dimension and large calculation. The predicted position of object centroid is updated and corrected by circle contour, forming prediction-measurement-updating closed-loop target tracking system. To reduce system processing time, on the premise of the tracking accuracy, a dynamic detection method based on target state prediction model is proposed. The results of contour extraction and underwater moving target experiments demonstrate the effectiveness of the proposed method.

Sensor Grid Enhancement with Data Management System for Ubiquitous Healthcare Computing

2013 ◽  
pp. 184-210
Author(s):  
Nikolaos Preve
Keyword(s):  
Data Management ◽  
Network Architecture ◽  
Management System ◽  
Data Access ◽  
Sensor Nodes ◽  
Data Management System ◽  
Biomedical Sensors ◽  
Communication Ability ◽  
Open Geospatial Consortium ◽  
Network Technologies

A Wireless Sensor Network (WSN) can be deployed to monitor the health of patients suffering from critical diseases. A wireless network consisting of biomedical sensors can also be implanted into the patient's body and can monitor the patients' conditions. These sensor devices, apart from having an enormous capability of collecting data from their physical surroundings, are also resource constraint in nature with a limited processing and communication ability. Therefore, it is necessary to integrate them with the Grid technology in order to process and store the collected data by the sensor nodes. This chapter proposes the SEnsor Grid Enhancement Data Management system, called SEGEDMA, ensuring the integration of different network technologies and the continuous data access to system users. The main contribution of this work is to achieve the interoperability of both technologies through a novel network architecture ensuring also the interoperability of Open Geospatial Consortium (OGC) and HL7 standards. According to the results SEGEDMA can be applied successfully in a decentralized healthcare environment.

Novel Energy Aware Algorithm to Design Multilayer Architecture for Dense Wireless Sensor Networks

2016 ◽  
pp. 79-114
Author(s):  
Naveen Chilamkurti ◽  
Sohail Jabbar ◽  
Abid Ali Minhas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Architecture ◽  
Network Performance ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Unbalanced Load

Network layer functionalists are of core importance in the communication process and so the routing with energy aware trait is indispensable for improved network performance and increased network lifetime. Designing of protocol at this under discussion layer must consider the aforementioned factors especially for energy aware routing process. In wireless sensor networks there may be hundreds or thousands of sensor nodes communicating with each other and with the base station, which consumes more energy in exchanging data and information with the additive issues of unbalanced load and intolerable faults. Two main types of network architectures for sensed data dissemination from source to destination exist in the literature; Flat network architecture, clustered network architecture. In flat architecture based networks, uniformity can be seen since all the network nodes work in a same mode and generally do not have any distinguished role.

Novel Energy Aware Algorithm to Design Multilayer Architecture for Dense Wireless Sensor Networks

2020 ◽  
pp. 372-399
Author(s):  
Naveen Chilamkurti ◽  
Sohail Jabbar ◽  
Abid Ali Minhas
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Architecture ◽  
Network Performance ◽  
Data Dissemination ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Unbalanced Load

Network layer functionalists are of core importance in the communication process and so the routing with energy aware trait is indispensable for improved network performance and increased network lifetime. Designing of protocol at this under discussion layer must consider the aforementioned factors especially for energy aware routing process. In wireless sensor networks there may be hundreds or thousands of sensor nodes communicating with each other and with the base station, which consumes more energy in exchanging data and information with the additive issues of unbalanced load and intolerable faults. Two main types of network architectures for sensed data dissemination from source to destination exist in the literature; Flat network architecture, clustered network architecture. In flat architecture based networks, uniformity can be seen since all the network nodes work in a same mode and generally do not have any distinguished role.

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