scholarly journals Bayesian Multidimensional Scaling for Location Awareness in Hybrid-Internet of Underwater Things

2021 ◽  
Author(s):  
Ruhul Amin Khalil ◽  
Nasir Saeed ◽  
Mohammad Inayatullah Khan Babar ◽  
Tariqullah Jan ◽  
Sadia Din
Keyword(s):  
Multidimensional Scaling ◽  
Magnetic Induction ◽  
Acoustic Waves ◽  
Communication Technologies ◽  
Sensor Nodes ◽  
Location Awareness ◽  
Underwater Communication ◽  
Navigation Data ◽  
Data Rates ◽  
Acoustic Technologies

<div> <div> <div> <p>Localization of sensor nodes in the Internet of Underwater Things (IoUT) is of considerable significance due to its various applications, such as navigation, data tagging, and detection of underwater objects. Therefore, in this paper, we propose a hybrid Bayesian multidimensional scaling (BMDS) based localization technique that can work on a fully hybrid IoUT network where the nodes can communicate using either optical, magnetic induction, and acoustic technologies. These communication technologies are already used for communication in the underwater environment; however, lacking localization solutions. Optical and magnetic induction communication achieves higher data rates for short communication. On the contrary, acoustic waves provide a low data rate for long-range underwater communication. The proposed method collectively uses optical, magnetic induction, and acoustic communication-based ranging to estimate the underwater sensor nodes’ final locations. Moreover, we also analyze the proposed scheme by deriving the hybrid Cramer-Rao lower bound (H-CRLB). Simulation results provide a complete comparative analysis of the proposed method with the literature. </p> </div> </div> </div>

scholarly journals Bayesian Multidimensional Scaling for Location Awareness in Hybrid-Internet of Underwater Things

2021 ◽  
Author(s):  
Ruhul Amin Khalil ◽  
Nasir Saeed ◽  
Mohammad Inayatullah Khan Babar ◽  
Tariqullah Jan ◽  
Sadia Din
Keyword(s):  
Multidimensional Scaling ◽  
Magnetic Induction ◽  
Acoustic Waves ◽  
Communication Technologies ◽  
Sensor Nodes ◽  
Location Awareness ◽  
Underwater Communication ◽  
Navigation Data ◽  
Data Rates ◽  
Acoustic Technologies

<div> <div> <div> <p>Localization of sensor nodes in the Internet of Underwater Things (IoUT) is of considerable significance due to its various applications, such as navigation, data tagging, and detection of underwater objects. Therefore, in this paper, we propose a hybrid Bayesian multidimensional scaling (BMDS) based localization technique that can work on a fully hybrid IoUT network where the nodes can communicate using either optical, magnetic induction, and acoustic technologies. These communication technologies are already used for communication in the underwater environment; however, lacking localization solutions. Optical and magnetic induction communication achieves higher data rates for short communication. On the contrary, acoustic waves provide a low data rate for long-range underwater communication. The proposed method collectively uses optical, magnetic induction, and acoustic communication-based ranging to estimate the underwater sensor nodes’ final locations. Moreover, we also analyze the proposed scheme by deriving the hybrid Cramer-Rao lower bound (H-CRLB). Simulation results provide a complete comparative analysis of the proposed method with the literature. </p> </div> </div> </div>

A Comparative Study of Computational Intelligence Algorithms for Sensor Localization

2019 ◽  
Vol 9 (2) ◽  
pp. 224-236
Author(s):  
Vaishali R. Kulkarni ◽  
Veena Desai ◽  
Raghavendra Kulkarni
Keyword(s):  
Firefly Algorithm ◽  
Heuristic Algorithms ◽  
Computing Time ◽  
Sensor Nodes ◽  
Convergence Time ◽  
Localization Error ◽  
Location Awareness ◽  
Cultural Algorithm ◽  
Localization Accuracy ◽  
Multi Stage

Background & Objective: Location of sensors is an important information in wireless sensor networks for monitoring, tracking and surveillance applications. The accurate and quick estimation of the location of sensor nodes plays an important role. Localization refers to creating location awareness for as many sensor nodes as possible. Multi-stage localization of sensor nodes using bio-inspired, heuristic algorithms is the central theme of this paper. Methodology: Biologically inspired heuristic algorithms offer the advantages of simplicity, resourceefficiency and speed. Four such algorithms have been evaluated in this paper for distributed localization of sensor nodes. Two evolutionary computation-based algorithms, namely cultural algorithm and the genetic algorithm, have been presented to optimize the localization process for minimizing the localization error. The results of these algorithms have been compared with those of swarm intelligence- based optimization algorithms, namely the firefly algorithm and the bee algorithm. Simulation results and analysis of stage-wise localization in terms of number of localized nodes, computing time and accuracy have been presented. The tradeoff between localization accuracy and speed has been investigated. Results: The comparative analysis shows that the firefly algorithm performs the localization in the most accurate manner but takes longest convergence time. Conclusion: Further, the cultural algorithm performs the localization in a very quick time; but, results in high localization error.

scholarly journals Magnetic Induction Technology-Based Wireless Sensor Network for Underground Infrastructure, Monitoring Soil Conditions, and Environmental Observation Applications: Challenges and Future Aspects

2022 ◽  
Vol 2022 ◽  
pp. 1-18
Author(s):  
Pratap Singh ◽  
Rishi Pal Singh ◽  
Yudhvir Singh ◽  
Jasgurpreet Singh Chohan ◽  
Shubham Sharma ◽  
...  
Keyword(s):  
Sensor Networks ◽  
Magnetic Induction ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Soil Conditions ◽  
Long Distance ◽  
Infrastructure Monitoring ◽  
Research Areas ◽  
Underground Infrastructure ◽  
Type Water

Wireless sensor networks (WSNs) especially with sensor nodes communicating with each other in medium other than air have been naive area of research since the last few years. In comparison to underwater communication, wireless underground sensor networks (WUSNs) are now being used in a large number of applications ranging from environmental observation, estimating chances of earthquake, communicating in underground tunnels or mines, and infrastructure monitoring to soil monitoring for agricultural purposes. In spite of all such promising applications, due to harsh and dynamically changing soil characteristics including soil type, water content in soil, and soil temperature, underground communication with conventional electromagnetic (EM) wave-based technology could not prove to be feasible for long-distance communication. Alternatively, due to magnetic permeability of soil being similar to air, magnetic induction- (MI-) based approach was adopted using magnetic coils as antenna for sensor nodes. Subsequently, MI waveguide and 3D coil mechanisms were considered to improve the system efficiency. Attributing to different characteristics of underlying transmission channels, communication protocols as well as architecture of MI-based WUSNS (MI-WUSNs) have been developed with different approaches. In this review paper, in addition to the latest advancements made for MI-WUSNs, closely associated areas of MI-WUSNs have also been explored. Additionally, research areas which are still open to be worked upon have been detailed out.

scholarly journals An Adaptable Train-to-Ground Communication Architecture Based on the 5G Technological Enabler SDN

Electronics ◽  
2019 ◽  
Vol 8 (6) ◽  
pp. 660 ◽  
Author(s):  
David Franco ◽  
Marina Aguado ◽  
Nerea Toledo
Keyword(s):  
Network Performance ◽  
Communication Technologies ◽  
Rolling Stock ◽  
Application Layer ◽  
Path Diversity ◽  
Communication Architecture ◽  
Multipath Tcp ◽  
Novel Approach ◽  
Data Rates ◽  
Current Systems

Railway communications are closely impacted by the evolution and availability of new wireless communication technologies. Traditionally, the critical nature of railway services, the long lifecycle of rolling stock, and their certification processes challenge the adoption of the latest communication technologies. A current railway telecom trend to solve this problem is to design a flexible and adaptable communication architecture that enables the detachment of the railway services—at the application layer—and the access technologies underneath, such as 5G and beyond. One of the enablers of this detachment approach is software-defined networking (SDN)—included in 5G architecture—due to its ability to programmatically and dynamically control the network behavior via open interfaces and abstract lower-level functionalities. In this paper, we design a novel railway train-to-ground (T2G) communication architecture based on the 5G technological enabler SDN and on the transport-level redundancy technique multipath TCP (MPTCP). The goal is to provide an adaptable and multitechnology communication service while enhancing the network performance of current systems. MPTCP offers end-to-end (E2E) redundancy by the aggregation of multiple access technologies, and SDN introduces path diversity to offer a resilient and reliable communication. We carry out simulation studies to compare the performance of the legacy communication architecture with our novel approach. The results demonstrate a clear improvement in the failover response time while maintaining and even improving the uplink and downlink overall data rates.

Signal Propagation and Analysis in Wireless Underground Sensor Networks

2019 ◽  
Vol 41 ◽  
pp. 60-78
Author(s):  
Adamu Murtala Zungeru ◽  
Joseph Chuma ◽  
Mmoloki Mangwala ◽  
Boyce Sigweni ◽  
Oduetse Matsebe
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Magnetic Induction ◽  
Signal To Noise Ratio ◽  
Path Loss ◽  
Signal Propagation ◽  
Pulse Power ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Nonlinear Program

The most challenging issue in the design of wireless sensor networks for the application of localization in the underground environment, mostly for miner’s location, is the sensor nodes’ energy consumption, efficiency and communication. Underground Wireless Sensor Networks are active and promising area of application of Wireless Sensor Networks (WSNs), whereby sensor nodes perform sensing duties in the underground environment. Most of the communication techniques used in the underground environment experience a high path loss and hence, hinders the range needed for transmission. However, the available option to increase information transmission is to increase the transmission power which needs large size of apparatus which is also limited in the underground. To solve the mentioned problems, this paper proposed a Magnetic Induction based Pulse Power. Analytical results of the Magnetic Induction based Pulse Power with an ordinary magnetic induction communication technique show an improvement in Signal-to-Noise Ratio (SNR) and path loss with variation in distance between nodes and frequency of operation. This paper further formulates a nonlinear program to determine the optimal data (events) extraction in a grid based WUSNs.

scholarly journals Altering the Course of Technologies to Monitor Loosening States of Endoprosthetic Implants

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 104 ◽  
Author(s):  
João Henrique Cachão ◽  
Marco P. Soares dos Santos ◽  
Rodrigo Bernardo ◽  
António Ramos ◽  
Rainer Bader ◽  
...  
Keyword(s):  
Magnetic Induction ◽  
Daily Living ◽  
Experimental Validation ◽  
Interface State ◽  
Bone Implant ◽  
Joint Replacements ◽  
Total Joint Replacements ◽  
Bioelectric Impedance ◽  
Societal Burden ◽  
Acoustic Technologies

Musculoskeletal disorders are becoming an ever-growing societal burden and, as a result, millions of bone replacements surgeries are performed per year worldwide. Despite total joint replacements being recognized among the most successful surgeries of the last century, implant failure rates exceeding 10% are still reported. These numbers highlight the necessity of technologies to provide an accurate monitoring of the bone–implant interface state. This study provides a detailed review of the most relevant methodologies and technologies already proposed to monitor the loosening states of endoprosthetic implants, as well as their performance and experimental validation. A total of forty-two papers describing both intracorporeal and extracorporeal technologies for cemented or cementless fixation were thoroughly analyzed. Thirty-eight technologies were identified, which are categorized into five methodologies: vibrometric, acoustic, bioelectric impedance, magnetic induction, and strain. Research efforts were mainly focused on vibrometric and acoustic technologies. Differently, approaches based on bioelectric impedance, magnetic induction and strain have been less explored. Although most technologies are noninvasive and are able to monitor different loosening stages of endoprosthetic implants, they are not able to provide effective monitoring during daily living of patients.

Using ZigBee in Ambient Intelligence Learning Scenarios

2012 ◽  
Vol 4 (3) ◽  
pp. 33-45
Author(s):  
Óscar García ◽  
Ricardo S. Alonso ◽  
Dante I. Tapia ◽  
Juan M. Corchado
Keyword(s):  
Information And Communication Technologies ◽  
Ambient Intelligence ◽  
Communication Technologies ◽  
Traditional Teaching ◽  
Location Awareness ◽  
Traditional Teaching Methods ◽  
Granularity Level ◽  
Information And Communication ◽  
Learning Scenarios ◽  
To Receive

The inclusion of Information and Communication Technologies, especially mobile devices, in learning environments has allowed both the emergence of new ways of learning and the adaptation of traditional teaching methods. In this sense, Ambient Intelligence (AmI) paradigm represents a promising approach that can be successfully applied to education. Pervasive computing, context and location awareness are AmI features that can allow students to receive customized information in a transparent way. Fortunately, there are several technologies that can help to gather such information. In this regard, Real-Time Locating Systems (RTLS) is a key technology that can improve context-awareness in AmI-based systems. This paper presents the use of a novel RTLS based on ZigBee technology that provides users’ positions in order to enhance context information in learning applications. This way, this system allows customizing the content offered to the users without their explicit interaction, as well as the granularity level provided by the system.

Research on Improved Multidimensional Scaling Localization Algorithm for Wireless Sensor Network

2010 ◽  
Vol 44-47 ◽  
pp. 3932-3936
Author(s):  
Liang Tao ◽  
Shuai Xu ◽  
Hai Yong Chen ◽  
He Xu Xun
Keyword(s):  
Multidimensional Scaling ◽  
Search Algorithm ◽  
Correction Method ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Wireless Sensor Nodes ◽  
Anchor Nodes ◽  
Hardware Configuration ◽  
Positioning Algorithm

Wireless sensor networks, which are energy limited, low hardware configuration and proneness to invalidation, puts a high demand on the positioning algorithm. Therefore the improved multidimensional scaling (IMDS) algorithm is proposed. In IMDS, firstly, local positioning areas (LPA) are established by an adaptive search algorithm. So the centralized multidimensional scaling (MDS) algorithm is changed into a distributed one. Then the shortest path distances between nodes on LPA are corrected with the geometric correction method (GCM) and adjusting weight correction method (AWCM). The distances between nodes become more accurate. Finally, with information of the public nodes of LPA and anchor nodes, we get the wireless sensor nodes coordinates through coordinate transformation by the SMACOF algorithm and the classical MDS algorithm.

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