Anomaly Detection Method for Sensor network in Under Water Environment

Nasrin, Fatema; Yasmin, Arifa; Ahmed, Nafiz Ishtiaque

doi:10.1109/icict4sd50815.2021.9396943

Cited by 9 publications

(3 citation statements)

References 13 publications

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“…The article [13] proposed an anomaly detection method for underwater sensor networks. This algorithm mainly represents the routing protocol by using the detection algorithm and modifying the routing path in the underwater wireless sensor networks, so as to reduce the number of damaged sensors.…”

Section: Literaturementioning

confidence: 99%

Survey of Connectivity Restoration in 3D Wireless Ad Hoc/Sensor Networks

Chen,

Wu,

et al. 2024

International Journal of Distributed Sensor Networks

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Wireless ad hoc/sensor networks (WASN) have seen increased application in three-dimensional (3D) environments, such as underwater and aerial scenarios. However, WASN may be fragmented or unable to connect continuously due to the harsh surrounding environment or high mobility. Therefore, restoring the network connectivity and transmit data in real time is very important. This paper focuses on the critical task of restoring network connectivity in 3D WASN, a complex issue given that existing connectivity restoration algorithms for two-dimensional environments are not directly applicable or become overly complicated in 3D contexts. We present a comprehensive analysis of the current research landscape, summarizing key findings related to various aspects of 3D WASN connectivity restoration. These aspects include the application environment (underwater, in the sky, and recovery disaster), opportunities for restoration (active, passive, and active/passive), implementation strategies (clustering and sleep scheduling), and resource constraints (node deployment and movement control). Our study also proposes a classification of connectivity restoration solutions for 3D WASN, identifying existing gaps and suggesting potential future research directions. By providing specific insights and a structured overview of the field, we aim to contribute to the ongoing development of robust and resilient 3D WASN.

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Section: Literaturementioning

confidence: 99%

Survey of Connectivity Restoration in 3D Wireless Ad Hoc/Sensor Networks

Chen,

Wu,

et al. 2024

International Journal of Distributed Sensor Networks

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“…One could consider the three imputation categories outlined by Zhang [2] as an optimization problem. The bio-inspired algorithms were extensively tested in the iterative imputation category for their balance of accuracy, development time and computing power.It is important to note that the majority of approaches to imputation of missing values involve bioinspired algorithms, machine learning algorithms for healthcare [3,4], ontology datasets for language processing [5], wireless communications [6], cognitive eye tracking systems [7].Although these algorithms are usually used to increase the intersection or to help with parameter adjustment instead of predicting the data themselves [8,9].…”

Section: Introductionmentioning

confidence: 99%

Transfer Learning Approach Applied to Data Imputation

Sultana¹

2022

Preprint

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The challenge of bearing fault diagnosis is great due to the large amount of data that needs to beanalysed. The goal of this analysis is to propose a good fit approach to dealing with faulty data inorder to optimize the correctness of data. A transfer learning method can be used to achieve this.Our study suggests that the transfer learning performs significantly better than other methods whenit comes to overcoming faulty bearing data. The transfer learning algorithm is accurate up to 90%of the time when trying to correct for this type of error.

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“…It might be challenging for those who lose their vision early to operate in society. This product's use might be detrimental to speech [1], language [2], and cognitive development [3,4] and machine learning [5]. For visual loss to be overcome, early detection is crucial.…”

Section: Introductionmentioning

confidence: 99%

The Ability to Detect Vision Loss from the Visual Cortex Using iEEG is a Key Advance in the Treatment of The Condition

Lee¹

2022

Preprint

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Individuals with early vision impairment often have difficulty navigating in the world. If you want to overcome your early vision misfortune, it's important to be distinct in your vision goals. This research can focus on recognizing vision misfortune early using EEG signals and light-sensitive receptors. The human vision method is difficult and troublesome to induce.The vision cortex is the part of the brain that plays an essential role in making ready vision knowledge in people. The vision framework may be a basic part of the body's overall framework, performing essential capacities and better vision abilities. This study is planned to look at the reasons for early vision misfortune and to study additional about the neural dynamics of the vision cortex.This information is essential for a variety of recovery and treatment options.

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Anomaly Detection Method for Sensor network in Under Water Environment

Cited by 9 publications

References 13 publications

Survey of Connectivity Restoration in 3D Wireless Ad Hoc/Sensor Networks

Survey of Connectivity Restoration in 3D Wireless Ad Hoc/Sensor Networks

Transfer Learning Approach Applied to Data Imputation

The Ability to Detect Vision Loss from the Visual Cortex Using iEEG is a Key Advance in the Treatment of The Condition

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