Fingerprint indoor positioning based on user orientations and minimum computation time

Firdaus, Firdaus; Ahmad, Noor Azurati; Sahibuddin, Shamsul

doi:10.12928/telkomnika.v17i4.12774

Cited by 8 publications

(8 citation statements)

References 34 publications

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“…Each database contains 8 samples for 100 people, i.e. for the analysis of deformities, there are three sets of 2800 natural deformations of fingerprints in total [25,26].…”

Section: Resultsmentioning

confidence: 99%

Development modeling methods of analysis and synthesis of fingerprint deformations images

AlKaraawi

Dhahir

Alameri³

et al. 2020

IJECE

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The current study is to develop modeling methods, Analysis and synthesis of fingerprints deformations images and their application in problems of automatic fingerprint identification. In the introduction justified urgency of the problem, is given a brief description of thematic publications. In this study will review of modern technologies of biometric technologies and methods of biometric identification, the review of fingerprint identification systems, investigate for distorting factors. The influence of deformations is singled out, the causes of deformation of fingerprints are analyzed. The review of modern ways of the account and modeling of deformations in problems of automatic fingerprint identification is given. The scientific novelty of the work is the development of information technologies for the analysis and synthesis of deformations of fingerprint images. The practical value of the work in the application of the developed methods, algorithms and information technologies in fingerprints identification systems. In addition, it has been found that our paper "devoted to research methods and synthesis of the fingerprint deformations" is a more appropriate choice than other papers.

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“…Each database contains 8 samples for 100 people, i.e. for the analysis of deformities, there are three sets of 2800 natural deformations of fingerprints in total [25,26].…”

Section: Resultsmentioning

confidence: 99%

Development modeling methods of analysis and synthesis of fingerprint deformations images

AlKaraawi

Dhahir

Alameri³

et al. 2020

IJECE

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show abstract

“…Yeo et al [24] use WiFi fingerprints at shopping malls in South of Kuala Lumpur, Malaysia. Firdaus et al [25] which use WiFi fingerprints based on user orientation to improve IPS. Another studies used Bluetooth (BLE) as transmitter, such as in Handojo et al [5], Asmus [26], Davies [27], Skårberg and Sletten [28], and Setiawan et al [29] that use it on the museum.…”

Section: Methodsmentioning

confidence: 99%

Indoor positioning system using BLE beacon to improve knowledge about museum visitors

et al. 2020

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Generally, a museum has many locations and artifacts collection that display for visitors. Museum manager often have difficulty in obtaining information on visitors behavior such as, is there are particular locations/artifacts in the museum that are frequently/rarely visit by museum visitors, how long visitors spend their time in particular locations/artifacts, etc. The purpose of this study is try to build a suitable system in order to improve knowledge about the behavior of museum visitors by identifying the position of visitors in the museum. This study uses Bluetooth Low Energy (BLE) Beacon that place around the museum. The visitor mobile phone will detect BLE beacon signal, then the mobile phone application will calculated the visitor's mobile phone position using the signal strength from the BLE beacons that are detected. The application then sends it to the computer server to display it in as museum visitor heat map. From this information, the museum manager could find out the visitors behavior movement and know which areas/artifacts that frequently/rarely visit by museum visitors. According to distance error testing which compare real location and position of the calculation, it is show that the average of distance error is around 140 cm. So, it can be concluded that the information obtained is sufficient enough to represent the position of museum visitors.

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“…The characteristic features of such measurements of the reference point will be evaluated and then recorded in the database. This iterative process will be performed at another reference point, and so on until all reference points are visited [25,26].…”

Section: Radio Frequency Pattern Matchingmentioning

confidence: 99%

“…Then, the measurements will compare with data in the server database according to the appropriate matching algorithm. The outcome of this process is likely to be the location of the mobile station [25,26]. The Figure 1 illustrates the principle of the two phases.…”

Section: Radio Frequency Pattern Matchingmentioning

confidence: 99%

Fingerprint positioning of users devices in long term evolution cellular network using K nearest neighbour algorithm

Alhasan

Abdulhussein

Khwayyir

2021

IJECE

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The rapid exponential growth in wireless technologies and the need for public safety has led to increasing demand for location-based services. Terrestrial cellular networks can offer acceptable position estimation for users that can meet the statutory requirements set by the Federal Communications Commission in case of network-based positioning, for safety regulations. In this study, the proposed radio frequency pattern matching (RFPM) method is implemented and tested to determine a user’s location effectively. The RFPM method has been tested and validated in two different environment. The evaluations show remarkable results especially in the Micro cell scenario, at 67% of positioning error 15m and at 90% 31.78m for Micro cell scenario, with results of 75.66m at 67% and 141.4m at 90% for Macro cell scenario.

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Fingerprint indoor positioning based on user orientations and minimum computation time

Cited by 8 publications

References 34 publications

Development modeling methods of analysis and synthesis of fingerprint deformations images

Development modeling methods of analysis and synthesis of fingerprint deformations images

Indoor positioning system using BLE beacon to improve knowledge about museum visitors

Fingerprint positioning of users devices in long term evolution cellular network using K nearest neighbour algorithm

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