Estimation of indoor position and motion direction for smartphones using DNN to BLE beacon signal strength

2020 ◽  
Author(s):  
Kaito Echizennya ◽  
Kazuhiro Kondo
Keyword(s):  
Signal Strength ◽  
Motion Direction ◽  
Beacon Signal

scholarly journals Dynamic Signal Strength Mapping and Analysis by Means of Mobile Geographic Information System

2017 ◽  
Vol 24 (4) ◽  
pp. 595-606 ◽  
Author(s):  
Marcin Kulawiak ◽  
Witold Wycinka
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Signal Strength ◽  
Geographic Information ◽  
Indoor Navigation ◽  
Mapping Algorithms ◽  
Target Environment ◽  
Online Storage ◽  
Beacon Signal

AbstractBluetooth beacons are becoming increasingly popular for various applications such as marketing or indoor navigation. However, designing a proper beacon installation requires knowledge of the possible sources of interference in the target environment. While theoretically beacon signal strength should decay linearly with log distance, on-site measurements usually reveal that noise from objects such as Wi-Fi networks operating in the vicinity significantly alters the expected signal range. The paper presents a novel mobile Geographic Information System for measurement, mapping and local as well as online storage of Bluetooth beacon signal strength in semireal time. For the purpose of on-site geovisual analysis of the signal, the application integrates a dedicated interpolation algorithm optimized for low-power devices. The paper discusses the performance and quality of the mapping algorithms in several different test environments.

scholarly journals Beacon Signal Strength Analysis for Efficient Indoor Positioning

2015 ◽  
Vol 19 (6) ◽  
pp. 552-557
Author(s):  
Hyun-seo Hwang ◽  
Jin-tae Park ◽  
Jun-soo Yun ◽  
Gyung-soo Phyo ◽  
Il-young Moon ◽  
...  
Keyword(s):  
Signal Strength ◽  
Indoor Positioning ◽  
Strength Analysis ◽  
Beacon Signal

Improved Contrast in Ultra-Low-Field MRI with Time-Dependent Bipolar Prepolarizing Fields: Theory and NMR Demonstrations

2013 ◽  
Vol 20 (3) ◽  
pp. 327-336 ◽  
Author(s):  
Jaakko O. Nieminen ◽  
Jens Voigt ◽  
Stefan Hartwig ◽  
Hans Jürgen Scheer ◽  
Martin Burghoff ◽  
...  
Keyword(s):  
Field Strength ◽  
Time Course ◽  
Signal Strength ◽  
Relaxation Rates ◽  
Resonance Imaging ◽  
New Approach ◽  
Spin Lattice ◽  
Low Field ◽  
Low Field Mri ◽  
Magnetic Resonance Imaging Mri

Abstract The spin-lattice (T1) relaxation rates of materials depend on the strength of the external magnetic field in which the relaxation occurs. This T1 dispersion has been suggested to offer a means to discriminate between healthy and cancerous tissue by performing magnetic resonance imaging (MRI) at low magnetic fields. In prepolarized ultra-low-field (ULF) MRI, spin precession is detected in fields of the order of 10-100 μT. To increase the signal strength, the sample is first magnetized with a relatively strong polarizing field. Typically, the polarizing field is kept constant during the polarization period. However, in ULF MRI, the polarizing-field strength can be easily varied to produce a desired time course. This paper describes how a novel variation of the polarizing-field strength and duration can optimize the contrast between two types of tissue having different T1 relaxation dispersions. In addition, NMR experiments showing that the principle works in practice are presented. The described procedure may become a key component for a promising new approach of MRI at ultra-low fields

KAJIAN KEKUATAN SINYAL RADIO (RSSI) XBEE DALAM RANGKA PEMASANGAN LANDSLIDE EARLY WARNING SYSTEM (LEWS) DI KABUPATEN GARUT, TASIKMALAYA DAN MAJALENGKA

2019 ◽  
Vol 3 (2) ◽  
pp. 88
Author(s):  
Riski Fitriani
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Received Signal Strength Indicator ◽  
Landslide Early Warning ◽  
Point To Point

Salah satu inovasi untuk menanggulangi longsor adalah dengan melakukan pemasangan Landslide Early Warning System (LEWS). Media transmisi data dari LEWS yang dikembangkan menggunakan sinyal radio Xbee. Sehingga sebelum dilakukan pemasangan LEWS, perlu dilakukan kajian kekuatan sinyal tersebut di lokasi yang akan terpasang yaitu Garut, Tasikmalaya, dan Majalengka. Kajian dilakukan menggunakan 2 jenis Xbee yaitu Xbee Pro S2B 2,4 GHz dan Xbee Pro S5 868 MHz. Setelah dilakukan kajian, Xbee 2,4 GHz tidak dapat digunakan di lokasi pengujian Garut dan Majalengka karena jarak modul induk dan anak cukup jauh serta terlalu banyak obstacle. Topologi yang digunakan yaitu topologi pair/point to point, dengan mengukur nilai RSSI menggunakan software XCTU. Semakin kecil nilai Received Signal Strength Indicator (RSSI) dari nilai receive sensitivity Xbee maka kualitas sinyal semakin baik. Pengukuran dilakukan dengan meninggikan antena Xbee dengan beberapa variasi ketinggian untuk mendapatkan kualitas sinyal yang lebih baik. Hasilnya diperoleh beberapa rekomendasi tinggi minimal antena Xbee yang terpasang di tiap lokasi modul anak pada 3 kabupaten.

Reduction of Acquisition Time for RIL, SDL, and LADA

2007 ◽  
Author(s):  
Arjan Mels ◽  
Frank Zachariasse
Keyword(s):  
Background Noise ◽  
Signal Strength ◽  
Acquisition Time ◽  
Optimal Conditions ◽  
Signal Collection ◽  
Defect Localization ◽  
Model Equations ◽  
Set Up ◽  
Main Operating ◽  
Quantitative Tool

Abstract Although RIL, SDL and LADA are slightly different, the main operating principle is the same and the theory for defect localization presented in this paper is applicable to all three methods. Throughout this paper the authors refer to LADA, as all experimental results in this paper were obtained with a 1064nm laser on defect free circuits. This paper first defines mathematically what 'signal strength' actually means in LADA and then demonstrates a statistical model of the LADA situation that explains the optimal conditions for signal collection and the parameters involved. The model is tested against experimental data and is also used to optimise the acquisition time. Through this model, equations were derived for the acquisition time needed to discern a LADA response from the background noise. The model offers a quantitative tool to estimate the feasibility of a given LADA measurement and a guide to optimising the required experimental set-up.

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