Early Steps in Automated Behavior Mapping via Indoor Sensors

Arsan, Taner; Kepez, Orcun

doi:10.3390/s17122925

Cited by 13 publications

(33 citation statements)

References 41 publications

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“…Before the MDEK1001 1 UWB sensors that were the main subject of this study, indoor positioning studies [28] were performed by using Wi-Fi, BLE beacons and TREK1000 2 UWB sensors. The aim of these studies was to minimize the average positioning error value as much as possible [28]. The results obtained from the studies in approximately 36 m 2 test areas reduced average positioning error values of 139 cm with Wi-Fi technology, 86 cm with BLE Beacon technology, and 24 cm with TREK1000 UWB sensors [28].…”

Section: Related Previous Workmentioning

confidence: 99%

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Accurate indoor positioning with ultra-wide band sensors

Arsan¹

2020

Turk J Elec Eng & Comp Sci

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Ultra-wide band is one of the emerging indoor positioning technologies. In the application phase, accuracy and interference are important criteria of indoor positioning systems. Not only the method used in positioning, but also the algorithms used in improving the accuracy is a key factor. In this paper, we tried to eliminate the effects of off-set and noise in the data of the ultra-wide band sensor-based indoor positioning system. For this purpose, optimization algorithms and filters have been applied to the raw data, and the accuracy has been improved. A test bed with the dimensions of 7.35 m × 5.41 m and 50 cm × 50 cm grids has been selected, and a total of 27,000 measurements have been collected from 180 test points. The average positioning error of this test bed is calculated as 16.34 cm . Then, several combinations of algorithms are applied to raw data. The combination of Big Bang-Big Crunch algorithm for optimization, and then the Kalman Filter have yielded the most accurate results. Briefly, the average positioning error has been reduced from 16.34 cm to 7.43 cm . Key words: Indoor positioning, ultra-wide band sensors, optimization, big bang-big crunch algorithm, genetic algorithms, the Kalman filter (A-GPS) technology is a navigation system used on mobile devices that helps to identify a user's location via the base station's A-GPS address server [3]. The accuracy provided by the GPS in determining the outdoor location is between 3 m and 15 m , usually around 10 m . The accuracy that A-GPS provides in determining the outdoor location is about 15 m, while the interior is 50 m [3]. As can be seen from the accuracy values, these solutions are sufficient to determine the outdoor position, in other words, the position in the open space.On the other hand, given the fact that people now spend more than 80% of their time indoors, a suitable system for locating interior space is needed. Unfortunately, the use of GPS satellites in indoor location determination is not possible as GPS signals are weaken due to atmospheric delays, multi-paths, steel structures, roofs and building walls [1][2][3]. For this reason, efforts have been made to develop new technologies that allow reliable indoor location determination with high accuracy, low average positioning error over the past two decades.

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Section: Related Previous Workmentioning

confidence: 99%

Section: Related Previous Workmentioning

confidence: 99%

Accurate indoor positioning with ultra-wide band sensors

Arsan¹

2020

Turk J Elec Eng & Comp Sci

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“…A special ceiling system shown in Figure 3 is developed to offer better LoS and also a direct path between the anchors and the tags [11]. e test user stayed in the test bed for at least 3 minutes providing 150 samples for each marked location.…”

Section: Experimental Setup and Indoor Positioning Datasetmentioning

confidence: 99%

“…us, at least some of them can go around or through obstacles. Hence, the UWB enables a more reliable and accurate positioning [10,11].…”

Section: Introductionmentioning

confidence: 99%

A Clustering-Based Approach for Improving the Accuracy of UWB Sensor-Based Indoor Positioning System

Arsan

Hameez

2019

Mobile Information Systems

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There are several methods which can be used to locate an object or people in an indoor location. Ultra-wideband (UWB) is a specifically promising indoor positioning technology because of its high accuracy, resistance to interference, and better penetration. This study aims to improve the accuracy of the UWB sensor-based indoor positioning system. To achieve that, the proposed system is trained by using the K-means algorithm with an additional average silhouette method. This helps us to define the optimal number of clusters to be used by the K-means algorithm based on the value of the silhouette coefficient. Fuzzy c-means and mean shift algorithms are added for comparison purposes. This paper also introduces the impact of the Kalman filter while using the measured UWB test points as an input for the Kalman filter in order to obtain a better estimation of the position. As a result, the average localization error is reduced by 43.26% (from 16.3442 cm to 9.2745 cm) when combining the K-means algorithm with the Kalman filter in which the Kalman-filtered UWB-measured test points are used as an input for the proposed system.

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“…Ultra geniş band teknolojisi, iç mekân konum belirleme uygulamalarında kullanıldığında ortalama hatanın 24 cm ile 30 cm arasında olduğu bilinmekle birlikte, bu hata seviyesi konum belirleme, yönlendirme ve navigasyon uygulamaları için yeterli doğruluğu görülmektedir. Davranış haritalama gibi uygulamalar ise daha yüksek doğruluğa ve daha düşük ortalama hata değerine ihtiyaç duymaktadırlar [36]. Geliştirilen yöntemden elde edilen sonuçlar davranış haritalama konusunda çok daha başarılı çalışmaların yapılmasına imkan sağlayacak niteliktedir.…”

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Improvement of Indoor Positioning Accuracy of Ultra-wide Band Sensors by Using Big Bang – Big Crunch Optimization Method

Arsan¹

2018

Pamukkale J Eng Sci

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Ultra geniş band teknolojisi, birçok iç mekân konum belirleme sisteminde başarılı çözümler sunan, diğer yöntemlere kıyasla daha iyi performans gösteren, gelişmekte olan bir teknolojidir. Bu çalışmada, ultra geniş band (Ultra Wide Band-UWB) sensörler kullanılarak bir iç mekân konum belirleme sistemi geliştirilmiş ve kullanılan ek algoritmalarla, standart donanımların sağladığı doğruluk düzeyi arttırılırken aynı zamanda ortalama hatayı azaltmak hedeflenmiştir. Bu amaçla Büyük Patlama-Büyük Çöküş (Big Bang-Big Crunch veya BB-BC) optimizasyon yöntemi deneysel iç mekân konumlandırma sistemine uygulanmış ve ölçüm doğruluğu üzerindeki olumlu etkisi yapılan testlerle kanıtlanmıştır. Test alanı olarak 7.35 m × 5.41 m boyutlarında 39.76 m 2 'lik bir alan seçilmiş ve özel olarak tasarlanmış bir tavan sistemine yerden 2.85 m yüksekliğe üç farklı UWB alıcı yerleştirilmiş ve 182 adet test noktasından 60 sn. süreyle toplam 10.920 ölçüm alınmıştır. Ölçüm sonuçları Büyük Patlama-Büyük Çöküş optimizasyon algoritması ile düzeltilerek, ortalama hatası önceki 20.72 cm değerinden 15.02 cm'ye düşürülmüş, böylelikle ölçüm sonuçlarının doğruluğu arttırılmıştır. Ultra-wide Band technology is an emerging technology that offers successful solutions in many indoor positioning systems and performs better than other methods. In this study, an indoor positioning system using Ultra-wide Band (UWB) sensors was developed and it was aimed to increase the accuracy level of the standard equipment with the additional algorithms used while reducing the average error. For this purpose, the Big Bang-Big Crunch (BB-BC) optimization method has been applied to the experimental indoor positioning system and the positive effect on the measurement accuracy has been proved by the tests made. An area of 39.76 m 2 was selected as a test area of 7.35 m × 5.41 m and three different Ultra-wide Band receivers were installed at a height of 2.85 m on a specially designed ceiling system and a total of 10.920 measurements were taken from 182 test points for 60 seconds. By correcting the measurement results with the Big Bang-Big Crunch optimization algorithm, the average error was reduced from the previous 20.72 cm to 15.02 cm, thus the accuracy of the measurement results were improved.

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Early Steps in Automated Behavior Mapping via Indoor Sensors

Cited by 13 publications

References 41 publications

Accurate indoor positioning with ultra-wide band sensors

Accurate indoor positioning with ultra-wide band sensors

A Clustering-Based Approach for Improving the Accuracy of UWB Sensor-Based Indoor Positioning System

Improvement of Indoor Positioning Accuracy of Ultra-wide Band Sensors by Using Big Bang – Big Crunch Optimization Method

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