Analysis of gradient-based cuckoo search for the large scale optimal rfid network planning

Hasnan, Khalid; Talib, Nihad Hasan; Nawawi, Azli

doi:10.1088/1742-6596/1150/1/012008

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…This section presents the evolutionary algorithm used to solve the multi-objective functions based on correlations between actual tag positions and RFID reader propagation rate. A modified cuckoo search algorithm is correlated with the gradient of the objective function for this task [26,27]. GBCS has proven to be a strong candidate algorithm for solving difficult optimization problems in large-scale areas.…”

Section: Gradient-based Cuckoo Search (Gbcs)mentioning

confidence: 99%

Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorithm (GBCS) Scheme

et al. 2020

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Condition monitoring is used as a tool for maintenance management and function as input to decision support. Thus the key parameters in preventing severe damage to railway assets can be determined by automatic real-time monitoring. The technique of radio-frequency identification (RFID) is increasingly applied for the automatic real-time monitoring and control of railway assets, which employs radio waves without the use of physical contact. In this work, a 243-km 2 area of Kuala Lumpur was selected. Because of its large size, determining the locations in which to install the RFID readers for monitoring the bogie components in the Kuala Lumpur railway system is a very complex task. The task involved three challenges: first, finding an optimal evolutionary method for railway network planning in order to deploy the RFID system in a large-area; second, identifying the large area that involved functional features; third, determining which station or stations should be given priority in applying the RFID system to achieve the most effective monitoring of the trains. The first challenge was solved by using a gradientbase cuckoo search algorithm for RFID system deployment. The second challenge was solved by determining all necessary information using geographic information system (GIS) resources. Because of the huge volume of data collected from GIS, it was found that the best method for eliminating data was to develop a new clustering model to separate the useful from the unuseful data and to identify the most suitable stations. Finally, the data set was reduced by developing a specific filter, and the information collected was tested by an analytic hierarchy process as a technique to determine the best stations for system monitoring and control. The results showed the success of the proposed method in solving the significant challenge of large-scale area conditions correlated with multi-objective RFID functions. The method provides high reliability in working with complex and dynamic data. Keywords Geographic information system (GIS) Á Analytic hierarchy process (AHP) Á Radio-frequency identification (RFID) Á Gradient-based cuckoo search algorithm (GBCS) Á Condition monitoring Á Bogie system Á Railway maintenance

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Section: Gradient-based Cuckoo Search (Gbcs)mentioning

confidence: 99%

Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorithm (GBCS) Scheme

et al. 2020

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“…The results of the nature-inspired algorithm were correlated with the tag positions in the functional hospital zone to acquire accurate information for five entities. The twodimensional plans used for the RFID network were based on the objective functions for a high RNP performance [15].…”

Section: Introductionmentioning

confidence: 99%

Real-time monitoring of clinic risks using an integrated RFID-FA scheme

Hussein

Fayyadh

2021

Bulletin EEI

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Patient safety is a global public health concern because of increases in the number of mistreatments due to the improper identification of patients or the improper administration of drugs. Risk in clinic management refers to the systematic process used to specify, control, and analyze organizational risks. The present article developed a new method to detect different objects automatically in real-time by monitoring and controlling the hospital workflow using radio frequency identification (RFID). The system methodology starts with identifying the functional area by detecting the room optical characters. Then clustering and matching the symmetrical functional area using histogram matching technique. For the monitoring process, the radio frequency network planning RNP has been used. Density-based scan algorithm (DBSCAN) was used for clustering and extracting the area, then all gathered data transferred to the firefly algorithm to track drug distribution and specify doctor and nurse locations. The simulation results observe real-time tracking and identification of people and drugs based on hospital zone designs. The results present 87% tag real-time coverage for managing and monitoring human inside the hospital. The effectiveness of this system shows that it was useful in monitoring clinic operations and effective for a hospital network solution.

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A new algorithm based CSP framework for RFID network planning

Jaballah

Meddeb

2020

J Ambient Intell Human Comput

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The huge growth of industrial society requires the deployment of radio frequency identification networks on a large scale. This necessitates the installation of a large number of radio frequency identification components (readers, tags, middleware and others). As a consequence, the cost and complexity of networks are increasing due to the large number of readers to be installed. Finding the optimal number, placement and parameters of readers to provide a high quality of service for radio frequency identification systems is a critical problem. A good planning affords a basic need for radio frequency identification networks, such as coverage, load balance and interference between readers. This problem is famous in the literature as a radio frequency identification network planning problem. All the proposed approaches in the literature have been based on meta-heuristics. In this paper, we design a new algorithm, called the RNP-CSP algorithm based on the constraint satisfaction problem framework to solve the radio frequency identification network planning problem. The performance evaluation shows that the RNP-CSP algorithm is more efficient than P S 2 O, GPSO and VNPSO-RNP.

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Analysis of gradient-based cuckoo search for the large scale optimal rfid network planning

Cited by 5 publications

References 2 publications

Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorithm (GBCS) Scheme

Monitoring Large-Scale Rail Transit Systems Based on an Analytic Hierarchy Process/Gradient-Based Cuckoo Search Algorithm (GBCS) Scheme

Real-time monitoring of clinic risks using an integrated RFID-FA scheme

A new algorithm based CSP framework for RFID network planning

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