Two Stage Grid Classification Based Algorithm for the Identification of Fields Under a Wireless Sensor Network Monitored Area

Panag, Tripatjot Singh; Dhillon, J.S.

doi:10.1007/s11277-016-3813-8

Cited by 6 publications

(4 citation statements)

References 59 publications

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“…The method improved the network coverage of the area by simulating the habits of different individuals in the social spider to schedule the network nodes, but the convergence of the algorithm is low. In literature [12], a maximum coverage hybrid search algorithm was proposed, which was based on the particle swarm optimization (PSO) algorithm to achieve global search and combined Hooke-Jeeves method to improve local search. By this, the method improved the convergence speed of the algorithm and optimized the area coverage of sensing nodes.…”

Section: Introductionmentioning

confidence: 99%

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Títul Research on Wireless Network Coverage for Transformation and Upgrading of Exhibition Management with Artificial Intelligence Technology

Dou

Zheng²

2023

Applied Mathematics and Nonlinear Sciences

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The rapid development of artificial intelligence and modern communication technology provides a powerful opportunity to realize the transformation, upgrading and high-quality development of exhibition management. To solve the optimal coverage problem of wireless network in the exhibition area, a new generation of artificial intelligence algorithm is introduced to propose a novel method for solving the network coverage problem based on Harris Hawk optimization (HHO) algorithm. From the perspective of maximizing coverage and minimizing coverage redundancy, the multi-objective coverage optimization problem of wireless network nodes is optimally extracted into a function and solved using the improved HHO (IHHO) algorithm. Through the simulation of the wireless network coverage in the exhibition area, the experimental results show that the comprehensive evaluation index score of the optimization algorithm reaches 98.03%, which is higher than the traditional particle swarm optimizer (PSO) and the standard HHO. The proposed IHHO algorithm can be effectively applied to the network coverage problem and has a greater advantage over the traditional optimization methods in terms of improving node coverage, and has great practicality.

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Section: Introductionmentioning

confidence: 99%

“…Peilin Dou and Guohua Zheng. Applied Mathematics and Nonlinear Sciences, 9(1) (2024)[1][2][3][4][5][6][7][8][9][10][11][12][13] …”

mentioning

confidence: 99%

Títul Research on Wireless Network Coverage for Transformation and Upgrading of Exhibition Management with Artificial Intelligence Technology

Dou

Zheng²

2023

Applied Mathematics and Nonlinear Sciences

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“…The methods of deployment in a network of connected objects can be classified into two categories: deterministic and random. In fact, random deployment is carried distributing sensor nodes randomly over the whole region of interest (RoI) [19,20]. This type of deployment is usually used in applications where the area to be monitored is too large or where the region of interest is inaccessible due to adverse and hazardous environmental conditions In this case, objects can be dispersed from an aircraft or by using multi-robot systems [21].…”

Section: Introductionmentioning

confidence: 99%

“…This type of deployment is usually used in applications where the area to be monitored is too large or where the region of interest is inaccessible due to adverse and hazardous environmental conditions In this case, objects can be dispersed from an aircraft or by using multi-robot systems [21]. To attain complete coverage, the random deployment technique requires more sensor nodes than the intended deployment [20].…”

Section: Introductionmentioning

confidence: 99%

Distributed Approach for the Indoor Deployment of Wireless Connected Objects by the Hybridization of the Voronoi Diagram and the Genetic Algorithm

Abdallah¹,

Mnasri²,

Val³

2022

J. Engg. Res. & Sci.

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IoT data collection networks have recently become one of the important research areas due to their fundamental role and wide application in many domains. The establishment of networks of objects is based essentially on the deployment of connected objects to process the collected data and transmit them to the various locations. Subsequently, a large number of nodes must be adequately deployed to achieve complete coverage. This manuscript introduces a distributed approach, which combines the Voronoi Diagram and the Genetic algorithm (VD-GA), to maximize the coverage of a region of interest. The Voronoi diagram is used to divide region into cells and generate initial solutions that present the positions of the deployed IoT objects. Then, a genetic algorithm is executed in parallel in several nodes to improve these positions. The developed VD-GA approach was evaluated on an experimental environment by prototyping on a real testbed utilizing M5StickC nodes equipped with ESP32 processor. The experiments show that the distributed approach provided better degree of coverage, RSSI, lifetime and number of neighboring objects than those given by the original algorithms in terms of the suggested distributed Genetic-Voronoi algorithm outperforms the centralized one in terms of speed of computing.

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Predator–prey optimization based clustering algorithm for wireless sensor networks

Panag

Dhillon

2021

Neural Comput & Applic

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Two Stage Grid Classification Based Algorithm for the Identification of Fields Under a Wireless Sensor Network Monitored Area

Cited by 6 publications

References 59 publications

Títul Research on Wireless Network Coverage for Transformation and Upgrading of Exhibition Management with Artificial Intelligence Technology

Títul Research on Wireless Network Coverage for Transformation and Upgrading of Exhibition Management with Artificial Intelligence Technology

Distributed Approach for the Indoor Deployment of Wireless Connected Objects by the Hybridization of the Voronoi Diagram and the Genetic Algorithm

Predator–prey optimization based clustering algorithm for wireless sensor networks

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