A fingerprint-based coarse-to-fine algorithm for indoor positioning system using Bluetooth Low Energy

Lie, Maximilianus Maria Kolbe; Kusuma, Gede Putra

doi:10.1007/s00521-020-05159-0

Cited by 22 publications

(8 citation statements)

References 24 publications

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“…A single smartphone transmitter moves around the office area, whereas their IPS models the motion of tracked objects, having no prior information about their movement. The positioning error rate in the worst-case scenario was around 3.15 m. Lie et al [37] proposed a coarse-to-fine fingerprint-based algorithm for location detection. Weighted sum and k-nearest neighbors with three different weight calculations are used in the coarse location estimation.…”

Section: Ble Indoor Localization Systemsmentioning

confidence: 99%

“…To detect nearby devices and receive data, it is necessary to use a communication module that supports BLE technology with a Bluetooth version equal to or higher than the one used on the transmitting side. Unlike Wi-Fi transmitters, which also transmit in the ISM band, BLE devices use only three advertising channels (37,38,39) and 37 data channels (0-36) spaced 2 MHz apart to prevent interference [57]. This also reduces power consumption, as only three channels need to be checked, so they are typically powered by cell batteries and have a lifetime of up to several years.…”

Section: Bluetooth Low Energy Beaconsmentioning

confidence: 99%

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Indoor Positioning System Based on Bluetooth Low Energy Technology and a Nature-Inspired Optimization Algorithm

2022

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Warehousing is one of the most important activities in the supply chain, enabling competitive advantage. Effective management of warehousing processes is, therefore, crucial for achieving minimal costs, maximum efficiency, and overall customer satisfaction. Warehouse Management Systems (WMS) are the first steps towards organizing these processes; however, due to the human factor involved, information on products, vehicles and workers may be missing, corrupt, or misleading. In this paper, a cost-effective Indoor Positioning System (IPS) based on Bluetooth Low Energy (BLE) technology is presented for use in Intralogistics that works automatically, and therefore minimizes the possibility of acquiring incorrect data. The proposed IPS solution is intended to be used for supervising order-picker movements, movement of packages between workstations, and tracking other mobile devices in a manually operated warehouse. Only data that are accurate, reliable and represent the actual state of the system, are useful for detailed material flow analysis and optimization in Intralogistics. Using the developed solution, IPS technology is leveraged to enhance the manually operated warehouse operational efficiency in Intralogistics. Due to the hardware independence, the developed software solution can be used with virtually any BLE supported beacons and receivers. The results of IPS testing in laboratory/office settings show that up to 98% of passings are detected successfully with time delays between approach and detection of less than 0.5 s.

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Section: Ble Indoor Localization Systemsmentioning

confidence: 99%

Section: Bluetooth Low Energy Beaconsmentioning

confidence: 99%

Indoor Positioning System Based on Bluetooth Low Energy Technology and a Nature-Inspired Optimization Algorithm

2022

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“…Media yang digunakan beragam. Mulai dari WiFi [5], Bluetooth [6], UWB [7], dan Radio [3] dengan karakteristik yang berbeda-beda. Berdasarkan berbagai pertimbangan mulai dari budget, tuntutan akurasi, sinyal gelombang radio, medan magnet, sinyal lampu dan akustik, kualitas Indoor Positioning System yang akan dipasang dapat ditentukan.…”

Section: Indoor Positioning Systemunclassified

Indoor Positioning System Berbasis Rfid Dengan Teknik Multilateration Dengan Optimasi Nelder Mead

Rabbani

Oklilas²,

Exaudi³

2022

Jusikom

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Indoor Positioning System (IPS) adalah teknologi untuk mengakomodasi pemetaan objek di dalam ruangan. Sistem ini dibuat tersendiri karena keterbatasan GPS untuk memetakan objek dalam ruangan karena terhalang oleh bangunan sehingga akurasi yang kurang presisi. RFID menjadi salah satu alternatif tag yang digunakan pada IPS karena mampu menghadirkan sistem pemetaan dengan biaya terjangkau dan performa yang tidak kalah jauh dari tag lainnya. Tujuan dari penelitian ini adalah untuk membangun sistem pemetaan dalam ruangan yang ekonomis dengan akurasi yang baik. Pada penelitian ini diajukan sebuah sistem IPS dengan objek pemetaan RFID Passive Tag dengan menggunakan Machine Learning Regresi yang diteruskan ke Multilateration yang selanjutnya dioptimalkan dengan algoritma Nelder Mead. Pada penelitian ini dibandingkan dua model regresi yaitu Support Vector Regression dan Linear Regression, prediksi jarak dari model terbaik akan dimasukkan pada persamaan Multilateration untuk memprediksi koordinat. Untuk meningkatkan akurasi dari teknik Multilateration digunakan optimasi algoritma Nelder Mead untuk mengatasi error dari prediksi jarak. Setelah dilakukan pengujian didapatkan akurasi dari model ini yaitu rerata error sebesar 37.39 cm.

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“…Because indoor spaces are more complex than outdoor environments in terms of layout, topology, and spatial constraints [3], indoor positioning requires higher accuracy [4]. In recent years, many indoor positioning systems have been proposed by researchers, which use different techniques, such as infrared [5], Wi-Fi [6], Bluetooth [7], optical [8], and inertial sensors [9]. However, each of these techniques has its application scenarios when considering accuracy, cost, coverage, complexity, and applicability.…”

Section: Introductionmentioning

confidence: 99%

Mobile Phone Indoor Scene Recognition Location Method Based on Semantic Constraint of Building Map

Liu¹,

Gao²,

Luo³

et al. 2022

Preprint

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At present, indoor localization is one of the core technologies of location-based services (LBS), and there exist numerous scenario-oriented application solutions. Visual features, as the main semantic information to help people understand the environment and thus occupy the dominant part, many techniques about indoor scene recognition are widely adopted. However, the engineering application problem of cell phone indoor scene recognition and localization has not been well solved due to insufficient semantic constraint information of building map and the immaturity of building map location anchors (MLA) matching positioning technology. To address the above problems, this paper proposes a cell phone indoor scene recognition and localization method with building map semantic constraints. Firstly, we build a library of geocoded entities for building map location anchors (MLA), which can provide users with "immersive" real-world building maps on the one hand and semantic anchor point constraints for cell phone positioning on the other. Secondly, using the improved YOLOv5s deep learning model carried on the mobile terminal, we recognize the universal map location anchors (MLA) elements in building scenes by cell phone camera video in real-time. Lastly, the spatial location of the scene elements obtained from the cell phone video recognition is matched with the building MLA to achieve real-time positioning and navigation. The experimental results show that the model recognition accuracy of this method is above 97.2%, and the maximum localization error is within the range of 0.775 m, and minimized to 0.5 m after applying the BIMPN road network walking node constraint, which can effectively achieve high positioning accuracy in the building scenes with rich MLA element information. In addition, the building map location anchors (MLA) has universal characteristics, and the positioning algorithm based on scene element recognition is compatible with the extension of indoor map data types, so this method has good prospects for engineering applications.

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A fingerprint-based coarse-to-fine algorithm for indoor positioning system using Bluetooth Low Energy

Cited by 22 publications

References 24 publications

Indoor Positioning System Based on Bluetooth Low Energy Technology and a Nature-Inspired Optimization Algorithm

Indoor Positioning System Based on Bluetooth Low Energy Technology and a Nature-Inspired Optimization Algorithm

Indoor Positioning System Berbasis Rfid Dengan Teknik Multilateration Dengan Optimasi Nelder Mead

Mobile Phone Indoor Scene Recognition Location Method Based on Semantic Constraint of Building Map

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