A Chaotic Parallel Artificial Fish Swarm Algorithm for Water Quality Monitoring Sensor Networks 3D Coverage Optimization

Zhou, Jie; Qi, Guohong; Liu, Changzheng

doi:10.1155/2021/5529527

Cited by 13 publications

(5 citation statements)

References 31 publications

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“…Zhou et al 63 developed a novel chaotic parallel artificial fish swarm method. An underwater 3D coverage model was created before the algorithm design to tackle the sensor coverage and monitoring challenges.…”

Section: Wireless Sensor Network That Operate Underwater—applicationsmentioning

confidence: 99%

Underwater acoustic sensor networks: Taxonomy on applications, architectures, localization methods, deployment techniques, routing techniques, and threats: A systematic review

Gola

Arya

2023

Concurrency and Computation

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SummaryWireless information routing beneath the ocean, or usually underwater, has supplied the most excellent technical methods of oceanic observations. Traditionally, ocean bottoms have been monitored by placing oceanographic sensors that collect data at specific and defined ocean zones. When the duties are performed, the oceanographic instruments are recovered. Because there is no collaborative exchange of collected data between the collecting point and the monitoring end, data cannot be observed remotely. Underwater sensor networks can be wirelessly connected with sensors and monitors without extensive cable. Underwater wireless sensor networks are what they are called (UWSNs). This article investigates the various aspects of UWSNs, such as their significance, applications, network design, demands, routing, deployments and challenges.

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Section: Wireless Sensor Network That Operate Underwater—applicationsmentioning

confidence: 99%

Underwater acoustic sensor networks: Taxonomy on applications, architectures, localization methods, deployment techniques, routing techniques, and threats: A systematic review

Gola

Arya

2023

Concurrency and Computation

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“…Wang et al [20] improved the coverage of sensor networks and reduced energy consumption by combining an improved PSO algorithm with grid division. Zhou et al [21] proposed a three-dimensional spatial coverage method based on Chaotic Parallel Artificial Fish Swarm Algorithm (CPAFSA), which had better performance compared with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). However, these methods relied on accurate position-ing and high-energy sensors, which were expensive in practical applications.…”

Section: Related Workmentioning

confidence: 99%

Lattice‐Based 3‐Dimensional Wireless Sensor Deployment

et al. 2021

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With the wide application of wireless sensor networks (WSNs) in real space, there are numerous studies on 3D sensor deployments. In this paper, the k -connectivity theoretical model of fixed and random nodes in regular lattice-based deployment was proposed to study the coverage and connectivity of sensor networks with regular lattice in 3D space. The full connectivity range and cost of the deployment with sensor nodes fixed in the centers of four regular lattices were quantitatively analyzed. The optimal single lattice coverage model and the ratio of the communication range to the sensing range r c / r s were investigated when the deployment of random nodes satisfied the k -connectivity requirements for full coverage. In addition, based on the actual sensing model, the coverage, communication link quality, and reliability of different lattice-based deployment models were determined in this study.

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“…Their aim was to enhance the accuracy of the mechanism model. In order to optimize the 3D target coverage of a underwater heterogeneous multi-sensor, Zhou et al [ 40 ] proposed a chaotic parallel artificial fish swarm algorithm (CPAFSA) to improve the coverage of underwater sensors and optimize the water quality-monitoring sensor network. CPAFSA uses chaos to select initialization parameters, adopts elite selection, effectively avoids local optimization, and integrates the global search function of parallel operators to solve the three-dimensional target coverage problem.…”

Section: Introductionmentioning

confidence: 99%

Damage Monitoring of Braided Composites Using CNT Yarn Sensor Based on Artificial Fish Swarm Algorithm

Wang

Jia

et al. 2023

Sensors

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This study aims to enable intelligent structural health monitoring of internal damage in aerospace structural components, providing a crucial means of assuring safety and reliability in the aerospace field. To address the limitations and assumptions of traditional monitoring methods, carbon nanotube (CNT) yarn sensors are used as key elements. These sensors are woven with carbon fiber yarns using a three-dimensional six-way braiding process and cured with resin composites. To optimize the sensor configuration, an artificial fish swarm algorithm (AFSA) is introduced, simulating the foraging behavior of fish to determine the best position and number of CNT yarn sensors. Experimental simulations are conducted on 3D braided composites of varying sizes, including penetration hole damage, line damage, and folded wire-mounted damage, to analyze the changes in the resistance data of carbon nanosensors within the damaged material. The results demonstrate that the optimized configuration of CNT yarn sensors based on AFSA is suitable for damage monitoring in 3D woven composites. The experimental positioning errors range from 0.224 to 0.510 mm, with all error values being less than 1 mm, thus achieving minimum sensor coverage for a maximum area. This result not only effectively reduces the cost of the monitoring system, but also improves the accuracy and reliability of the monitoring process.

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A Chaotic Parallel Artificial Fish Swarm Algorithm for Water Quality Monitoring Sensor Networks 3D Coverage Optimization

Cited by 13 publications

References 31 publications

Underwater acoustic sensor networks: Taxonomy on applications, architectures, localization methods, deployment techniques, routing techniques, and threats: A systematic review

Underwater acoustic sensor networks: Taxonomy on applications, architectures, localization methods, deployment techniques, routing techniques, and threats: A systematic review

Lattice‐Based 3‐Dimensional Wireless Sensor Deployment

Damage Monitoring of Braided Composites Using CNT Yarn Sensor Based on Artificial Fish Swarm Algorithm

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