Fingerprinting Acoustic Localization Indoor Based on Cluster Analysis and Iterative Interpolation

Wang, Shuopeng; Yang, Peng; Sun, Hao

doi:10.3390/app8101862

Cited by 4 publications

(3 citation statements)

References 30 publications

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“…Therefore, we used the catastrophe progression method to quantify the indicators of each layer of China's NEV industry development capability mutation system model, and comprehensively evaluated the indicators to obtain a ranking of each company. In order to understand the development capability of China's NEV industry from a macro perspective, we used cluster analysis to further cluster the 15 companies based on the evaluation results [56] and obtain more intuitive analysis results.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of the Development Capability of the New Energy Vehicle Industry: An Empirical Study from China

Meng

Jin

2019

Sustainability

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In order to alleviate the pressures of environmental pollution and the energy crisis, and to lay out and capture huge emerging markets as soon as possible, all countries in the world are vigorously developing new energy vehicles (NEVs). This paper analyzes the factors influencing the development capability of the NEV industry from the aspects of autonomy, controllability, and stability, and constructs an evaluation index system. Based on the improved entropy method and the catastrophe progression method, we establish an evaluation model for the development capability of China’s NEV industry and comprehensively evaluate the development capability of 15 new energy auto companies. An empirical analysis finds that the outlook for the overall development capability of China’s NEV industry is not optimistic, and there is a big gap in the industry, lacking core technology and independent innovation capability. We propose countermeasures such as increasing research and development (R&D) investment and innovation, and improving policy support.

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Section: Methodsmentioning

confidence: 99%

Evaluation of the Development Capability of the New Energy Vehicle Industry: An Empirical Study from China

Meng

Jin

2019

Sustainability

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“…In the conventional fingerprinting or flat-based fingerprinting localization, the computational complexity grows with the size of the radio map (number of RPs on the radio map) [3], [22]. For N RPs on the testbed, the computational complexity of traditional fingerprinting localization (linear matching process) is O(N ) [40], [41]. However, the complexity of localization estimation process based on cluster analysis (every cluster having the same number of RPs) is O(N /H ), where H is the total number of exemplars.…”

Section: ) Rss Clustering Using Apcmentioning

confidence: 99%

Improving Indoor Fingerprinting Positioning With Affinity Propagation Clustering and Weighted Centroid Fingerprint

Subedi

Gang

et al. 2019

IEEE Access

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Nowadays, research and development of various indoor positioning systems (IPS) have been increasing owing to flourishing social and commercial interest in location-based services (LBSs). Among LBS technologies, we used the Bluetooth low energy beacon in our system, which consumes less energy and is embedded in many current smartphones and tablets. In particular, the fingerprinting method has become a prime choice in the design of IPS owing to its good location estimation and the fact that a line-of-sight from access points is not required. We propose an improved two-step fingerprinting localization using multiple fingerprint features to enhance the localization accuracy. The proposed system uses a propagation model to convert RSS of beacons to distance and estimate the weighted centroid (WC) of nearby beacons. The estimated WCs along with signal strength and rank of the nearby beacons are stored in the server database for localization instead of RSS from all the deployed beacons. First, the proposed system makes use of diverse fingerprinting features to increase localization accuracy that also reduces both the physical size of the database and the amount of data communication with the server in the execution phase; second, affinity propagation clustering minimizes the searching space of RPs and reduces the computational cost; third, exponential averaging is introduced to smooth the noisy RSS. The experimental results obtained by real field deployment show that the proposed method significantly improves the performance of the positioning system in both the positioning accuracy and radio-map database size. INDEX TERMS Affinity propagation clustering, BLE, Exponential averaging, RSS, Weighted centroid.

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“…Bo et al [26] presents a study on the acoustics of the Syracuse open-air theatre, with experiments and simulations. A room acoustic experiment is proposed by Wang et al in [27] to investigate fingerprinting acoustic localization indoors.…”

Section: Modelling Simulation and Data Analysis In Acoustical Problemsmentioning

confidence: 99%

Special Issue on Modelling, Simulation and Data Analysis in Acoustical Problems

Guarnaccia

Tronchin

Viscardi³

2019

Applied Sciences

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Fingerprinting Acoustic Localization Indoor Based on Cluster Analysis and Iterative Interpolation

Cited by 4 publications

References 30 publications

Evaluation of the Development Capability of the New Energy Vehicle Industry: An Empirical Study from China

Evaluation of the Development Capability of the New Energy Vehicle Industry: An Empirical Study from China

Improving Indoor Fingerprinting Positioning With Affinity Propagation Clustering and Weighted Centroid Fingerprint

Special Issue on Modelling, Simulation and Data Analysis in Acoustical Problems

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