Multi-objective sensor placement using the effective independence model (SPEM) for wireless sensor networks in structural health monitoring

Elsersy, Mohamed; Ahmed, Mohamed H.; Elfouly, Tarek; Abdaoui, Abderrazak

doi:10.1109/iwcmc.2015.7289147

Cited by 7 publications

(16 citation statements)

References 13 publications

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“…One can see in Table 8 that whenever the quality information needed increases, more sensors are required to be placed. And this matches what is found in literature [14], [15], and [16]. Validation:…”

Section: Results Of Implementing Brute Force On a Five-sensors Story supporting

confidence: 90%

“…But the solutions used in the listed research are general and did not consider civil requirements. However, other research works do consider civil engineering requirements to optimize sensor placement in addition to network needs, as in [14], [15], [16], [17], [18], and others. The above-mentioned research greatly contributed to this field, but if investigated further, we notice that they never considered minimizing the number of sensors as part of the solution for the sensor placement problem.…”

Section: Overviewmentioning

confidence: 99%

“…determinant that is a standard metric to identify the sensor placement quality in civil engineering [27], [14], [15]. In addition to that, In another work, improvement was done to p-SPEM in [16]. Multi objective p-SPEM (mop-SPEM) algorithm for sensor deployment was suggested.…”

Section: Sensor Placement Based On Civil Engineering and Network Requmentioning

confidence: 99%

“…The mathematical formulation for the thesis problem depends on the system model in [14], [15], [16], and [42]. The Euclidean distance considered in this research between sensor node and sensor node is given as follows:…”

Section: Preliminariesmentioning

confidence: 99%

“…In this research work, our experiments are conducted using three mode shapes as used in literature [15] and [14]. In addition to that, three mode shapes are advised and recommended by people in civil engineering for a typical and normal tower 16 where they informed that the mostly used mode shapes are the first three out of 12. Figure 13: The effect of increasing the number of mode shapes on a five-story building 15 The number of mode shapes K checked out is based on the available data we can get.…”

Section: Relation Between Number Of Mode Shapes and Number Of Sensorsmentioning

confidence: 99%

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Minimising number of sensors in wireless sensor networks for structure health monitoring systems

El-Qawasma

Elfouly

Ahmed

2019

IET wirel. sens. syst.

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Nowadays, wireless sensor networks (WSNs) are considered an essential candidate to apply structural health monitoring (SHM). An important problem in this area is sensor placement optimization. In many research works, solving this problem focuses only on the network properties and requirements such as energy consumption, network coverage, …etc., without considering the civil engineering requirements. However, there are other research works that consider network and civil requirements while optimizing the sensor placement. Unfortunately, although minimizing the number of sensors is important, it has never been addressed. This could be noticed from the limited literature found that addresses this problem while considering both the civil and the network requirements. As a result, in this thesis we study the problem of minimizing the number of sensors for SHM in WSNs. The idea behind this research is to reduce the network size, which can solve some problems such as the scalability, installation time and cost. Our contribution in this work is not limited to the mathematical model of the mentioned problem, but will extend to solve the problem using different methods: the exhaustive search, genetic algorithm (GA), and a heuristic algorithm that applies the binary search. The problem is then solved for different number of sensors as well as different placements in many conducted experiments. Finally, the time complexity is evaluated to compare between all the applied methods. The obtained results showed that minimizing the number of sensors becomes more significant with big structures. Furthermore, the binary search algorithm is the best to use to solve the problem for small buildings. But, For larger buildings, there is a trade-off between the performance, and time complexity, where

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Section: Results Of Implementing Brute Force On a Five-sensors Story supporting

confidence: 90%

Section: Overviewmentioning

confidence: 99%

Section: Sensor Placement Based On Civil Engineering and Network Requmentioning

confidence: 99%

Section: Preliminariesmentioning

confidence: 99%

Section: Relation Between Number Of Mode Shapes and Number Of Sensorsmentioning

confidence: 99%

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Minimising number of sensors in wireless sensor networks for structure health monitoring systems

El-Qawasma

Elfouly

Ahmed

2019

IET wirel. sens. syst.

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A Review on Multi-objective Optimization in Wireless Sensor Networks Using Nature Inspired Meta-heuristic Algorithms

Gunjan

2022

Neural Process Lett

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Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization

Ding

et al. 2018

Applied Soft Computing

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In Wireless Sensor Networks (WSN), maintaining a high coverage and extending the network lifetime are two conflicting crucial issues considered by real world service providers. In this paper, we consider the coverage optimization problem in WSN with three objectives to strike the balance between network lifetime and coverage. These include minimizing the energy consumption, maximizing the coverage rate and maximizing the equilibrium of energy consumption. Two improved hybrid multi-objective evolutionary algorithms, namely Hybrid-MOEA/D-I and Hybrid-MOEA/D-II, have been proposed. Based on the well-known MOEA/D algorithm, Hybrid-MOEA/D -I hybrids a genetic algorithm and a differential evolutionary algorithm to effectively optimize sub-problems of the multi-objective optimization problem in WSN. By integrating a discrete particle swarm algorithm, we further enhance solutions generated by Hybrid-MOEA/D-I in a new Hybrid-MOEA/D-II algorithm. Simulation results show that the proposed Hybrid-MOEA/D-I and Hybrid-MOEA/D-II algorithms have a significantly better performance compared with existing algorithms in the literature in terms of all the objectives concerned.

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Multi-objective sensor placement using the effective independence model (SPEM) for wireless sensor networks in structural health monitoring

Cited by 7 publications

References 13 publications

Minimising number of sensors in wireless sensor networks for structure health monitoring systems

Minimising number of sensors in wireless sensor networks for structure health monitoring systems

A Review on Multi-objective Optimization in Wireless Sensor Networks Using Nature Inspired Meta-heuristic Algorithms

Hybrid multi-objective evolutionary algorithms based on decomposition for wireless sensor network coverage optimization

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