Relevant bibliographies by topics / RFID Network Planning

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'RFID Network Planning'

Author: Grafiati
Published: 3 June 2025
Last updated: 13 July 2025

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Journal articles on the topic "RFID Network Planning"

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Guo, Dong Liang, Qiao Xiang, and Zhong Hua Li. "Hybrid Intelligent Optimization Approach for RFID Network Planning." Applied Mechanics and Materials 596 (July 2014): 230–33. http://dx.doi.org/10.4028/www.scientific.net/amm.596.230.

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Radio Frequency Identification (RFID) is a kind of short-range radio technology for data acquisition and automatic identification. In large scale application of RFID system, RFID network planning (RNP) is one of the fundamental tasks need to be fulfilled. This paper proposed an efficient hybrid intelligent optimization approach for RNP. A RNP optimization model is designed in considering of coverage, cost, and the radiated power of readers. A hybrid intelligent optimization approach is proposed to optimize the model in a hierarchical fashion. Firstly, we used the intelligent optimization algorithm to regulate the number and position of the RFID readers for the coverage and cost objective. Then, the optimal radiate power of readers is computed by analytic calculation. Experimental results show that this hybrid intelligent optimization approach has the advantage in terms of the quality of RFID network deployment and computation efficiency comparing with the existing approaches.
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Ait Lhadj Lamin, S., A. Raghib, and B. Abou El Majd. "Robust multi-objective optimization for solving the RFID network planning problem." Mathematical Modeling and Computing 8, no. 4 (2021): 616–26. http://dx.doi.org/10.23939/mmc2021.04.616.

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Radio-frequency identification (RFID) is a new technology used for identifying and tracking objects or people by radio-frequency waves to facilitate automated traceability and data collection. The RFID system consists of an electronic tag attached to an object, readers, and a middleware. In the latest real applications based on the RFID technology, the deployment of readers has become a central issue for RFID network planning by means of optimizing several objectives such as the coverage of tags, the number of readers, and the readers/tags interferences. In practice, the system is affected by uncertainty and uncontrollable environmental parameters. Therefore, the optimal solutions to the RFID network planning problem can be significantly reduced with uncontrollable variations in some parameters, such as the reader's transmitted power. In this work, we propose a robust multi-objective optimization approach to solve the deployment of RFID readers. In this way, we achieve robust optimal solutions that are insensitive to uncertainties in the optimization parameters.
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Qasim Mohammed, Shaymaa, Mohammed Najm Abdullah, and Ahmed Sabah Al-Araji. "One decade of radio frequency identification (RFID) Network Planning (RFID-NP)." Measurement: Sensors 26 (April 2023): 100696. http://dx.doi.org/10.1016/j.measen.2023.100696.

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Raghib, Abdelkader, and Badr Abou El Majd. "Multi-Objective Decision Aid Application for RFID Network Planning." MATEC Web of Conferences 200 (2018): 00017. http://dx.doi.org/10.1051/matecconf/201820000017.

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The Radio Frequency Identification system (RFID) is a generic term for technologies of a type of automatic identification system that use radio-frequency waves to automatically identify people or objects. Multiple RFID readers are required to detect and monitor the tags in the network area due to their limited interrogation range. Therefore, the cost of the RFID System, its efficiency in the communication process, and the number of tags covered directly depend on the number of deployed readers. In this work, we present a new many/multi-objective model with the aim to achieve the optimal solutions of the NP-hard problem of RFID Network Planning (RNP). The model involves many objectives and constraints as determining the minimum number of readers, finding their optimal 3D deployment and localization, guarantying a full coverage of all the tags distributed in the area, and minimizing the energy and the interferences caused by an overlap in the readers signals and the tags responds at the same time. Moreover, we provide a new decision aid application with the aim to access, manage, solve, and optimize the RNP problem involving the needs of researchers and decision makers.
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Hoa, Le Van, Nguyen Van Tung, and Vo Viet Minh Nhat. "An Approach to Hopfield Network-Based Energy-Efficient RFID Network Planning." Cybernetics and Information Technologies 24, no. 2 (2024): 50–66. http://dx.doi.org/10.2478/cait-2024-0015.

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Abstract Radio Frequency IDentification (RFID) Network Planning (RNP) is the problem of placing RFID readers in a working area where a tag is interrogated by at least one reader and at the same time satisfies some constraints such as minimum number of placed readers, minimal interference, and minimal outside coverage. The RNP optimization has been proven NP-hard; thus, natural-inspired approaches are often used to find the optimal solution. The paper proposes an energy-efficient RNP approach in which the positions of placed readers are optimized by a Hopfield network, and the energy efficiency is achieved through a placement area restriction technique. A mechanism of redundant reader elimination is also added to minimize the number of placed readers. Simulation results show that the Hopfield network-based energy-efficient RNP approach achieves the maximum tag coverage and energy efficiency by reducing interference, outside coverage, and the number of placed readers.
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Ait Lhadj Lamin, S., A. Raghib, and B. Abou El Majd. "An effective approach in robustness optimization for solving the RFID network planning problem with uncertainty." Mathematical Modeling and Computing 11, no. 1 (2024): 70–83. http://dx.doi.org/10.23939/mmc2024.01.070.

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RFID technology enables remote storage and retrieval of data on RFID tags, making it a versatile and efficient tool with widespread applications in various industries. This paper presents a solution to the challenge of deploying RFID readers, which has been a persistent problem in the RFID technology practical and theoretical communities. To address the deployment problem, the paper proposes a robust multi-objective approach that optimizes many requested objectives as: coverage, the number of deployed readers, and interference while taking into account uncontrollable parameters in the system. The simulation results demonstrate the robustness of the approach in solving the deployment problem and optimizing the RFID system under varying and unpredictable conditions. The proposed approach has the potential to contribute to the RFID technology industry and enable more efficient and effective RFID systems across different sectors.
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Huda, Huda, and Farah Q. Abdullah AL AL-Khalidi. "Evaluation Software and IT Integration for IoT-based Healthcare Radio Frequency Identification Network Planning." Fusion: Practice and Applications 15, no. 2 (2024): 288–97. http://dx.doi.org/10.54216/fpa.150224.

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For Internet of Things (IoT)-based on healthcare systems to autonomously monitor patients, radio frequency identification, or RFID, its essential. It is difficult to guarantee complete coverage throughout sizable healthcare facilities with a small number of RFID readers, though Software for RFID network planning must be optimized. The purpose of this paper is about optimizing related software and suggest a topological RFID network planning strategy that will minimize reader interference while deploying the fewest possible readers. The best location for RFID tags on patients as well as readers depends on the layout of the institution and how the patients move. To dependably scan tags across a variety of locations, RFID network design software precisely calculates the number and positions of readers using algorithms. Software features and network planning goals are developed to efficiently track patient status by automating the gathering of medical data. in this paper to find the optimal number of RFID readers required and their location in the system. After the algorithm was tested, it was found that the algorithm can determine the true effectiveness of the coverage and reduce the area of interference between the areas of coverage of RFID readers. PSO is a superior algorithm for solving difficult problems (NP). The PSO algorithm has shown a high efficiency in finding the optimal solution, with some of weakness in the performance of the algorithm, represented in finding functional boundaries that serve the research problem. By providing constant access to health information, this plan raises the standard of care.
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Chen, Hanning, Yunlong Zhu, Lianbo Ma, and Ben Niu. "Multiobjective RFID Network Optimization Using Multiobjective Evolutionary and Swarm Intelligence Approaches." Mathematical Problems in Engineering 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/961412.

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The development of radio frequency identification (RFID) technology generates the most challenging RFID network planning (RNP) problem, which needs to be solved in order to operate the large-scale RFID network in an optimal fashion. RNP involves many objectives and constraints and has been proven to be a NP-hard multi-objective problem. The application of evolutionary algorithm (EA) and swarm intelligence (SI) for solving multiobjective RNP (MORNP) has gained significant attention in the literature, but these algorithms always transform multiple objectives into a single objective by weighted coefficient approach. In this paper, we use multiobjective EA and SI algorithms to find all the Pareto optimal solutions and to achieve the optimal planning solutions by simultaneously optimizing four conflicting objectives in MORNP, instead of transforming multiobjective functions into a single objective function. The experiment presents an exhaustive comparison of three successful multiobjective EA and SI, namely, the recently developed multiobjective artificial bee colony algorithm (MOABC), the nondominated sorting genetic algorithm II (NSGA-II), and the multiobjective particle swarm optimization (MOPSO), on MORNP instances of different nature, namely, the two-objective and three-objective MORNP. Simulation results show that MOABC proves to be more superior for planning RFID networks than NSGA-II and MOPSO in terms of optimization accuracy and computation robustness.
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Chen, Hanning, Yunlong Zhu, Kunyuan Hu, and Tao Ku. "RFID network planning using a multi-swarm optimizer." Journal of Network and Computer Applications 34, no. 3 (2011): 888–901. http://dx.doi.org/10.1016/j.jnca.2010.04.004.

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Heba, M. Elewe*. "ANGULAR BASED MODEL FOR RFID NETWORK PLANNING FOR WAREHOUSE MANAGEMENT SYSTEM." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 4, no. 10 (2017): 132–37. https://doi.org/10.5281/zenodo.1034499.

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Large scale warehouses often apply the RFID Network Planning (RNP) strategy to efficiently track assets, which can lead to significant revenue gain. For this reason, this research has developed a three dimension RFID network planning model that can improve warehouse management. The mathematical model of the RFID network planning is concerned with two major issues. The first one is the correlation between the reader height and the rack levels. The second issue is to specify the optimal tag coverage based on the elliptical interrogation reader range. The DBFA algorithm is used as a method to evaluate the deterministic indicators in NP hard problems. The current work has provided much superior results for three dimension large scale condition and observed the effectiveness in traditional warehouse layout. The research has presented a new perspective in achieving maximum volumetric coverage with optimal number of deployed readers.
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Dissertations / Theses on the topic "RFID Network Planning"

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Tsai, Hsing Fang, and 蔡幸芳. "Improved Genetic Algorithm for RFID Reader Network Planning Problem." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/08906341784328249885.

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碩士<br>長庚大學<br>電機工程學系<br>101<br>In recent years, radio frequency identification (RFID) technique has been widely used in many applications. The RFID system consists of two types of devices, tags and readers. The area for a reader to identify tags is called the interrogation zone. Due to the limited interrogation range of the communication between the reader and the tag, the deployment of minimum number of readers to cover all tags in the entire region is known as the RFID reader network planning (RNP) problem. In general, the RNP problem is a type of resource allocation problems, which is a combinational optimization problem. In this paper, we propose a traditional genetic algorithm (TGA) to solve the RNP problem but this TGA is computational-time-consuming and does not guarantee to cover all of tags in the entire region. To overcome this point, we propose an improved genetic algorithm (IGA) which involved Micro-GA, correction mechanism and space crossover to solve this RNP problem. We have tested the proposed IGA on several RNP problems and compare with a traditional genetic algorithm (TGA) and a particle swarm optimization (PSO) method by solving the same RNPs. The comparison results demonstrate that the proposed IGA outperforms the TGA and the PSO method.
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Kang, Da Jhou, and 康大洲. "Comparisons of Three Heuristic Method for Three-Dimensional RFID Reader Network Planning Problems." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/qbmar5.

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碩士<br>長庚大學<br>電機工程學系<br>105<br>In recent years, radio frequency identification (RFID) technique has been widely used in various fields. Due to the limited interrogation zone, how to use the minimum reader to cover all the tags in the space to form the Reader Network Planning (RNP) problem. In this thesis, we proposed genetic algorithm (GA)、micro genetic algorithm (mGA) and particle swarm optimization (PSO) to solve the three-dimensional space reader network planning problem. Due to the traditional genetic algorithm and the traditional particle swarm optimization do not guarantee 100% tag coverage. To overcome the point, we proposed the correction scheme to guarantee 100% tag coverage. In addition, we proposed the spatial crossover to replace the traditional crossover of genetic algorithm and a micro genetic algorithm to improve the search ability. The comparison results show that the algorithms with correction scheme have 100% tag coverage.
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林林弘. "An EPC Network based RFID Information Architecture Planning – A Case Study of Car Bumper Supply Chain." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/70500866417168970633.

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碩士<br>國立清華大學<br>工業工程與工程管理學系工程碩士在職專班<br>95<br>The EPCglobal organization found a RFID information architecture named ‘EPC Network’ was based on EPC (Electronic Product code). The concept of EPC Network is ‘Internet of things’, every object was given a unique identification code stored at RFID tag, using mature internet architecture to reach “Internet of Physical Objects”. With EPC Network, we can connecting every object and create the vision of “Identify any object anywhere automatically”. lthough the standards of EPC Network have not been completed by EPCglobal organization, but the functions of core services were defined and having done several specifications and documents. This study of exploring EPC Network architecture planning in car bumper supply chain, and extend the researches by Zeng(2005)、Liu(2006). Three phases of this study： 1.Phase one：Collection the current RFID applications in automobile industry and use these applications as references to planning a EPC Network based of car bumper supply chain. 2.Phase two： Study the combination、materials flow、issues、RFID implementation point and RFID implementation values between OEM Market and After Market in car bumper supply chain. 3.Phase three：Drill into the RFID information architecture after RFID data capture equipments were implemented, such as information function、core components needed for each supply chain member、data structure、data transfer type、interoperation between members. Keyword：RFID、EPC Network、Supply Chain、Electronic Pedigree
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"Modeling, Analysis, and Efficient Resource Allocation in Cyber-Physical Systems and Critical Infrastructure Networks." Doctoral diss., 2016. http://hdl.handle.net/2286/R.I.40732.

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abstract: The critical infrastructures of the nation are a large and complex network of human, physical and cyber-physical systems. In recent times, it has become increasingly apparent that individual critical infrastructures, such as the power and communication networks, do not operate in isolation, but instead are part of a complex interdependent ecosystem where a failure involving a small set of network entities can trigger a cascading event resulting in the failure of a much larger set of entities through the failure propagation process. Recognizing the need for a deeper understanding of the interdependent relationships between such critical infrastructures, several models have been proposed and analyzed in the last few years. However, most of these models are over-simplified and fail to capture the complex interdependencies that may exist between critical infrastructures. To overcome the limitations of existing models, this dissertation presents a new model -- the Implicative Interdependency Model (IIM) that is able to capture such complex interdependency relations. As the potential for a failure cascade in critical interdependent networks poses several risks that can jeopardize the nation, this dissertation explores relevant research problems in the interdependent power and communication networks using the proposed IIM and lays the foundations for further study using this model. Apart from exploring problems in interdependent critical infrastructures, this dissertation also explores resource allocation techniques for environments enabled with cyber-physical systems. Specifically, the problem of efficient path planning for data collection using mobile cyber-physical systems is explored. Two such environments are considered: a Radio-Frequency IDentification (RFID) environment with mobile “Tags” and “Readers”, and a sensor data collection environment where both the sensors and the data mules (data collectors) are mobile. Finally, from an applied research perspective, this dissertation presents Raptor, an advanced network planning and management tool for mitigating the impact of spatially correlated, or region based faults on infrastructure networks. Raptor consolidates a wide range of studies conducted in the last few years on region based faults, and provides an interface for network planners, designers and operators to use the results of these studies for designing robust and resilient networks in the presence of spatially correlated faults.<br>Dissertation/Thesis<br>Doctoral Dissertation Computer Science 2016
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Book chapters on the topic "RFID Network Planning"

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Azizi, Aydin. "RFID Network Planning." In Applications of Artificial Intelligence Techniques in Industry 4.0. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2640-0_3.

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Wang, Jun, Jinsong Chen, Qianying Liu, and Jia Liu. "HCO-Based RFID Network Planning." In Communications in Computer and Information Science. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-2829-9_40.

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XU, He, Weiwei SHEN, Peng LI, and Cong QIAN. "An Efficient RFID Reader Network Planning Strategy Based on P2P Computing." In Advances on P2P, Parallel, Grid, Cloud and Internet Computing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49109-7_36.

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Gao, Xiang, and Ying Gao. "TDMA Grouping Based RFID Network Planning Using Hybrid Differential Evolution Algorithm." In Artificial Intelligence and Computational Intelligence. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16527-6_15.

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Tuba, Milan, Nebojsa Bacanin, and Marko Beko. "Multiobjective RFID Network Planning by Artificial Bee Colony Algorithm with Genetic Operators." In Advances in Swarm and Computational Intelligence. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20466-6_27.

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Raghib, Abdelkader, Badr Abou El Majd, and Brahim Aghezzaf. "An Optimal Deployment of Readers for RFID Network Planning Using NSGA-II." In Operations Research/Computer Science Interfaces Series. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-58253-5_27.

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Zhang, Zhongwei, Junfei Ren, Zhengzheng Dai, Bohui Zhang, Lihui Wu, and Zhaoyun Wu. "Research on RFID Network Planning Based on Directional and Omnidirectional Antenna Readers." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70665-4_129.

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Le, Van Hoa, Thanh Chuong Dang, Hong Quoc Nguyen, and Viet Minh Nhat Vo. "An Integrated Model of Placement Optimization and Redundancy Elimination in RFID Network Planning." In The 12th Conference on Information Technology and Its Applications. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36886-8_29.

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Gu, Qiwei, Kai Yin, Ben Niu, and Hanning Chen. "RFID Networks Planning Using BF-PSO." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31576-3_24.

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Anusha, S., and Sridhar Iyer. "RFIDcover – A Coverage Planning Tool for RFID Networks with Mobile Readers." In Embedded and Ubiquitous Computing – EUC 2005 Workshops. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596042_107.

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Conference papers on the topic "RFID Network Planning"

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Al-Naima, Fawzi M., and Raoof T. Hussein. "PSO Based Indoor RFID Network Planning." In 2013 International Conference on Developments in eSystems Engineering (DeSE). IEEE, 2013. http://dx.doi.org/10.1109/dese.2013.11.

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Tuba, Milan, Nebojsa Bacanin, and Marko Beko. "Fireworks algorithm for RFID network planning problem." In 2015 25th International Conference Radioelektronika (RADIOELEKTRONIKA. IEEE, 2015. http://dx.doi.org/10.1109/radioelek.2015.7129049.

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Niu, Ben, Edward C. Wong, Yujuan Chai, and Li Li. "RFID Network Planning Based on MCPSO Alogorithm." In 2009 International Symposium on Information Science and Engineering (ISISE). IEEE, 2009. http://dx.doi.org/10.1109/isise.2009.37.

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Dimitriou, Antonis G., Stavroula Siachalou, Aggelos Bletsas, and John N. Sahalos. "Automated RFID network planning with site-specific stochastic modeling and particle Swarm Optimization." In 2014 IEEE International Conference on RFID-Technologies and Applications (RFID-TA). IEEE, 2014. http://dx.doi.org/10.1109/rfid-ta.2014.6934198.

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Suriya, Atipong, and J. David Porter. "Genetic algorithm based approach for RFID network planning." In TENCON 2014 - 2014 IEEE Region 10 Conference. IEEE, 2014. http://dx.doi.org/10.1109/tencon.2014.7022427.

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Bacanin, Nebojsa, Milan Tuba, and Raka Jovanovic. "Hierarchical multiobjective RFID network planning using firefly algorithm." In 2015 International Conference on Information and Communication Technology Research (ICTRC). IEEE, 2015. http://dx.doi.org/10.1109/ictrc.2015.7156477.

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Guan, Qiang, Yu Liu, Yiping Yang, and Wenshneg Yu. "Genetic Approach for Network Planning in the RFID Systems." In Sixth International Conference on Intelligent Systems Design and Applications. IEEE, 2006. http://dx.doi.org/10.1109/isda.2006.253899.

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Hasnan, Khalid, Aftab Ahmed, Badrul-aisham, and Qadir Bakhsh. "Optimization of RFID network planning using Zigbee and WSN." In PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON CONDENSED MATTER PHYSICS 2014 (ICCMP 2014). AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4915852.

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Tuba, Milan, Nebojsa Bacanin, and Adis Alihodzic. "Firefly algorithm for multi-objective RFID network planning problem." In 2014 22nd Telecommunications Forum Telfor (TELFOR). IEEE, 2014. http://dx.doi.org/10.1109/telfor.2014.7034365.

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hasnan, Khalid Bin, Nihad Hasan Talib, Azli Bin Nawawi, Adel Muhsin Elewe, Haslina Binti Abdullah, and Suhaidah Tahir. "An efficient algorithm for large-scale RFID Network Planning." In 2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT). IEEE, 2019. http://dx.doi.org/10.1109/jeeit.2019.8717490.

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