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- 摘要
- 关键词
- 实验方案
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[IEEE 2018 Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS) - Wuhan (2018.3.22-2018.3.23)] 2018 Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS) - Image Processing Based Indoor Localization System for Assisting Visually Impaired People
摘要： Indoor localization or indoor positioning system is a known as a process of detecting position of any object or people inside a building or room by different sensory data collected from different devices using different techniques such as radio waves, magnetic fields, acoustic signals or other procedures. However, lacking of a standard localization system is still a very big concern. Solution of this issue can be very beneficial for people in many cases but it can be especially very beneficial for the visually impaired people. In this paper, an image processing based indoor localization system has been developed using OpenCV and Python by following color detection technique to detect position of the user with maximum accuracy and then location of user is determined by analyzing that location matrix. Location accuracy depends on the size of the matrix and successful identification of target color. Firebase real time database was added to the system which made real time operations between server and the user end device easier. To justify the proposed model, successful experiments were conducted in indoor environments as well and correct result was achieved each time by detecting accurate locations. This will be very advantageous to observe the fully or partially sightless people and guide them towards their destination and also to inspect them for their security purpose.
关键词： Color Segmentation,Indoor localization,Image Processing,Indoor positioning system,Wireless communication,Connected object detection
更新于2025-09-23 15:23:52
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Optical Wireless Communication Based Indoor Positioning Algorithms: Performance Optimisation and Mathematical Modelling
摘要： In this paper, the performance of the optimal beam radius indoor positioning (OBRIP) and two-receiver indoor positioning (TRIP) algorithms are analysed by varying system parameters in the presence of an indoor optical wireless channel modelled in line of sight configuration. From all the conducted simulations, the minimum average error value obtained for TRIP is 0.61 m against 0.81 m obtained for OBRIP for room dimensions of 10 m × 10 m × 3 m. In addition, for each simulated condition, TRIP, which uses two receivers, outperforms OBRIP and reduces position estimation error up to 30%. To get a better understanding of error in position estimation for different combinations of beam radius and separation between light emitting diodes, the 90th percentile error is determined using a cumulative distribution frequency (CDF) plot, which gives an error value of 0.94 m for TRIP as compared to 1.20 m obtained for OBRIP. Both algorithms also prove to be robust towards change in receiver tilting angle, thus providing flexibility in the selection of the parameters to adapt to any indoor environment. In addition, in this paper, a mathematical model based on the concept of raw moments is used to confirm the findings of the simulation results for the proposed algorithms. Using this mathematical model, closed-form expressions are derived for standard deviation of uniformly distributed points in an optical wireless communication based indoor positioning system with circular and rectangular beam shapes.
关键词： position estimation,channel modelling,raw moments,optical wireless communication,indoor positioning system,cumulative distribution frequency,standard deviation
更新于2025-09-23 15:22:29
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[Institution of Engineering and Technology 12th European Conference on Antennas and Propagation (EuCAP 2018) - London, UK (9-13 April 2018)] 12th European Conference on Antennas and Propagation (EuCAP 2018) - Remote Vital Sign Recognition through Machine Learning augmented UWB
摘要： This paper describes an experimental demonstration of machine learning (ML) techniques supplementing radar to distinguish and detect vital signs of users in a domestic environment. This work augments an intelligent location awareness system previously proposed by the authors. That research employed Ultra-Wide Band (UWB) radar complemented by supervised machine learning techniques to remotely identify a person’s room location via ?oor plan training and time stamp correlations. Here, the remote breathing and heartbeat signals are analyzed through Short Term Fourier Transformation (STFT) to determine the Micro-Doppler signature of those vital signs in different room locations. Then, Multi-Class Support Vector Machine (MC-SVM) is implemented to train the system to intelligently distinguish between vital signs during different activities. Statistical analysis of the experimental results supports the proposed algorithm. This work could be used to further understand, for example, how active older people are by engaging in typical domestic activities.
关键词： Short Term Fourier Transform (STFT),Breathing,Ultra-Wide Band (UWB),Multi-Class Support Vector Machine (MC-SVM),Heartbeat,Indoor Positioning System (IPS)
更新于2025-09-23 15:22:29
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Experimental Indoor Visible Light Positioning Systems with Centimeter Accuracy Based on A Commercial Smartphone Camera
摘要： We consider indoor positioning based on visible light where the receiver adopts a commercial smartphone camera. Two positioning approaches are proposed, either the light emitting diode (LED) positions are known or not. When the LED positions are known, the LED light signal intensities are measured to identify the identity (ID) of each LED in the image. Triangular similarity is adopted to estimate the receiver position. When the LED positions are unknown, we develop a shift rotation model on the receiver movement and further propose a novel indoor positioning algorithm. The algorithm estimates the rotation center in the image instead of treating the image center as the rotation center, leading to reduced positioning error. To achieve high accuracy, a location reference point is set such that the positioning errors of multiple LEDs have little effect. According to the experimental results, the average positioning error can be reduced to 1cm, which outperforms the reported experimental results with receiver-ceiling distance larger than 2m.
关键词： visible light,LED,camera,Indoor positioning system
更新于2025-09-11 14:15:04
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[IEEE 2018 IEEE International Conference on Electro/Information Technology (EIT) - Rochester, MI (2018.5.3-2018.5.5)] 2018 IEEE International Conference on Electro/Information Technology (EIT) - Evaluation of Indoor Positioning Technologies for Prototyping at Kettering University
摘要： This paper presents research performed on indoor positioning technologies to identify a technology that would be best to implement in a prototype at Kettering University’s campus. The indoor positioning techniques evaluated are mainly based including Bluetooth, Wi-Fi, Geomagnetic, Visual Light Communication (VLC), and Ultra- Wideband (UW). Target-side wearable sensors will be considered. The algorithms commonly used for calculating the user’s position will be discussed, including Trilateration, Fingerprinting, and K- Nearest-Neighbor.
关键词： Visual Light Communication,Ultra-Wideband,Geomagnetic,Trilateration,K-nearest-neighbor,Fingerprinting,Indoor Positioning System,Wi-Fi,Bluetooth
更新于2025-09-09 09:28:46