Integrity and Multimedia Data Management using Emerging Technologies in the Healthcare Applications-Part II

2021 ◽  
Vol 14 (7) ◽  
pp. 698-699
Author(s):  
Ashutosh Sharma
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intelligent Systems ◽  
Emerging Technologies ◽  
Detection Algorithm ◽  
Multimedia Data ◽  
Corner Detection ◽  
Wireless Sensor ◽  
Future Research ◽  
Special Issue

In the present era of research and technology, several emerging concepts, like Wireless Sensor Networks (WSN), Body Wireless Sensor Networks (BWSN), Internet of Things (IoT), Cloud, Fog, Edge, SDN, and Big Data Analytics, can support IoT for design and development of intelligent systems in diverse domains. This special issue aims to concentrate on all aspects and future research directions related to this specific area of multimedia-based emerging technologies. We received 22 manuscripts in total for this special issue across the globe, and after the rigorous review process, only 5 manuscripts have been accepted for publication. The commitments for this Special Issue are reviewed as follows: Feng Zhao and Gaurav Dhiman contribute an article titled “Analysis of Data Point Cloud Preprocessing and Feature Angle Detection Algorithm” In this paper, the theory of computer vision and reverse engineering has been used to obtain the data of the segmented hull with the method of digitizing the physical parts. The simulation results show that the efficiency of the edge extraction algorithm based on mathematical morphology is 30%, which is found to be higher than the mesh generation method. An adaptive corner detection algorithm based on the edge can adaptively determine the size of the support area and accurately detect the corner position [1].......

scholarly journals A Low-Cost Jamming Detection Approach Using Performance Metrics in Cluster-Based Wireless Sensor Networks

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1179
Author(s):  
Carolina Del-Valle-Soto ◽  
Carlos Mex-Perera ◽  
Juan Arturo Nolazco-Flores ◽  
Alma Rodríguez ◽  
Julio C. Rosas-Caro ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Performance Metrics ◽  
Low Cost ◽  
Detection Algorithm ◽  
Anomalous Behavior ◽  
Wireless Sensor ◽  
Jamming Detection ◽  
Minimal Energy Expenditure

Wireless Sensor Networks constitute an important part of the Internet of Things, and in a similar way to other wireless technologies, seek competitiveness concerning savings in energy consumption and information availability. These devices (sensors) are typically battery operated and distributed throughout a scenario of particular interest. However, they are prone to interference attacks which we know as jamming. The detection of anomalous behavior in the network is a subject of study where the routing protocol and the nodes increase power consumption, which is detrimental to the network’s performance. In this work, a simple jamming detection algorithm is proposed based on an exhaustive study of performance metrics related to the routing protocol and a significant impact on node energy. With this approach, the proposed algorithm detects areas of affected nodes with minimal energy expenditure. Detection is evaluated for four known cluster-based protocols: PEGASIS, TEEN, LEACH, and HPAR. The experiments analyze the protocols’ performance through the metrics chosen for a jamming detection algorithm. Finally, we conducted real experimentation with the best performing wireless protocols currently used, such as Zigbee and LoRa.

scholarly journals Distributed Beacon Drifting Detection for Localization in Unstable Environments

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Ming Xia ◽  
Peiliang Sun ◽  
Xiaoyan Wang ◽  
Yan Jin ◽  
Qingzhang Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Detection Algorithm ◽  
Experimental Results ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Location Information ◽  
Detection Accuracy ◽  
Research Issue ◽  
Fundamental Research

Localization is a fundamental research issue in wireless sensor networks (WSNs). In most existing localization schemes, several beacons are used to determine the locations of sensor nodes. These localization mechanisms are frequently based on an assumption that the locations of beacons are known. Nevertheless, for many WSN systems deployed in unstable environments, beacons may be moved unexpectedly; that is, beacons are drifting, and their location information will no longer be reliable. As a result, the accuracy of localization will be greatly affected. In this paper, we propose a distributed beacon drifting detection algorithm to locate those accidentally moved beacons. In the proposed algorithm, we designed both beacon self-scoring and beacon-to-beacon negotiation mechanisms to improve detection accuracy while keeping the algorithm lightweight. Experimental results show that the algorithm achieves its designed goals.

scholarly journals Differentiated Service Model-Supported Cluster-Based Routing in Wireless Sensor Networks

2020 ◽  
Vol 3 ◽  
pp. 1-9
Author(s):  
Jayashree Agarkhed ◽  
Patil Yogita Dattatraya ◽  
Siddarama R. Patil
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Multimedia Data ◽  
Wireless Sensor ◽  
Differentiated Service ◽  
Healthcare Applications ◽  
Network Failure ◽  
Critical Data ◽  
Cluster Based Routing ◽  
Time Critical

Wireless Sensor Network finds its extensive use in healthcare applications for the transfer of time-critical data through wireless connectivity. The primary cause of network failure is the transfer of time-critical multimedia data. The article presents a new differentiated service modelsupported (DSM) cluster-based routing in wireless sensor networks (WSNs) that overcomes the above issue. DSM prioritizes the transfer of different flow types based on packet type and packet size. The employment of computational offloading minimizes delay for critical and small-sized data packets and by carrying out data reduction of large-sized packets at proxy server. It outperforms the existing protocols in terms of energy efficiency, throughput, and reliability by prioritizing the transfer of time-critical health application data

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