Research on RTLS-Based Coordinate Guided Vehicle (CGV) for Material Distribution in Discrete Manufacturing Workshop

Jiang, Jiajun; Guo, Yu; Liao, Wenhe; Li, Siguo; Xie, Xinping; Yuan, Liuyin; Nian, Liyun

doi:10.1109/ithings.2014.10

Cited by 9 publications

(5 citation statements)

References 9 publications

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“…The value of β typically falls within the interval [2,4] [5] (2 in free space and 4 in adverse indoor environments). In this work we consider β = 2, since we consider signal propagation in free space, without reflections or reverberations .…”

Section: Problem Formulationmentioning

confidence: 99%

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Elephant Herding Optimization for Energy-Based Localization

Correia¹,

Beko²,

Cruz³

et al. 2018

Preprint

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This work addresses the energy-based source localization problem in wireless sensors networks. Instead of circumventing the maximum likelihood (ML) problem by applying convex relaxations and approximations (like all existing approaches do), we here tackle it directly by the use of metaheuristics. To the best of our knowledge, this is the first time that metaheuristics is applied to this type of problems. More specifically an elephant herding optimization (EHO) algorithm is applied. Through extensive simulations, the key parameters of the EHO algorithm are optimized such that they match the energy decay model between two sensor nodes. A detailed analysis of the computational complexity is presented, as well as performance comparison between the proposed algorithm and existing non-metaheuristic ones. Simulation results show that the new approach significantly outperforms the existing solutions in noisy environments, encouraging further improvement and testing of metaheuristic methods.

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Section: Problem Formulationmentioning

confidence: 99%

“…To obtain the energy observations at the i th sensor, we average the readings over M signal measurements according to (2), i.e.,…”

Section: Problem Formulationmentioning

confidence: 99%

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Elephant Herding Optimization for Energy-Based Localization

Correia¹,

Beko²,

Cruz³

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…Thus, with current solutions, real-time identification and localization of containers are error-prone activities that still require human intervention to manage anomalous situations (for example, by physically searching the containers that are out of place). In order to overcome these limitations, several works have been proposed to add tracking and tracing capabilities to localization techniques by using wireless sensor networks [14,35,62]. WSNs have proven to be useful in different scenarios, from human activity recognition [47,48] to ambient assisted living [46] as well as for general purpose indoor localization systems [6,9].…”

Section: Localization Tracking and Identificationmentioning

confidence: 99%

Evaluating the impact of smart technologies on harbor’s logistics via BPMN modeling and simulation

et al. 2016

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A smart Information and Communication Technology (ICT) enables a synchronized interplay of different key factors, aligning infrastructures, consumers, and governmental policy-making needs. In the harbor's logistics context, smart ICT has been driving a multiyear wave of growth. Although there is a standalone value in the technological innovation of a task, the impact of a new smart technology is unknown without quantitative analysis methods on the end-to-end process. In this paper, we first present a review of the smart ICT for marine container terminals, and then we propose to evaluate the impact of such smart ICT via Business Process Model and Notation (BPMN) modeling and simulation. The proposed approach is discussed in a real-world modeling and simulation analysis, made on a pilot terminal of the Port of Leghorn (Italy).

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“…[1,2,3,4]. In general, source localization algorithms can be categorized as range-free and range-based [5,6,7,8].…”

Section: Introductionmentioning

confidence: 99%

Elephant Herding Optimization for Energy-Based Localization

Correia

Beko

Cruz

et al. 2018

Sensors

View full text Add to dashboard Cite

This work addresses the energy-based source localization problem in wireless sensors networks. Instead of circumventing the maximum likelihood (ML) problem by applying convex relaxations and approximations, we approach it directly by the use of metaheuristics. To the best of our knowledge, this is the first time that metaheuristics are applied to this type of problem. More specifically, an elephant herding optimization (EHO) algorithm is applied. Through extensive simulations, the key parameters of the EHO algorithm are optimized such that they match the energy decay model between two sensor nodes. A detailed analysis of the computational complexity is presented, as well as a performance comparison between the proposed algorithm and existing non-metaheuristic ones. Simulation results show that the new approach significantly outperforms existing solutions in noisy environments, encouraging further improvement and testing of metaheuristic methods.

show abstract

Research on RTLS-Based Coordinate Guided Vehicle (CGV) for Material Distribution in Discrete Manufacturing Workshop

Cited by 9 publications

References 9 publications

Elephant Herding Optimization for Energy-Based Localization

Elephant Herding Optimization for Energy-Based Localization

Evaluating the impact of smart technologies on harbor’s logistics via BPMN modeling and simulation

Elephant Herding Optimization for Energy-Based Localization

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