The Estimation of the Potential for Using Smart-Trackers as a Part of a Medical Indoor-Positioning System

This research aims to estimate the feasibility of using smart-bracelets as a part of a medicine indoor-positioning system, to monitor the health status and location of patients in a hospital. The smart-bracelet takes on the role of a token of the system and can measure pulse, blood pressure and saturation and provide data transmission over the BLE. The distance between token and anchor was calculated by the RSSI. The position of a token and anchor relative to each other was determined by the trilateration method. The results of the research showed that the accuracy of the developed system in a static position is 1.46 m and exceeds 3 m in a dynamic position. Results of experiments showed that measurements from the smart bracelets are transmitted to the server of the system without distortion. The study results indicated that smart-bracelets could be used to locate patients inside a hospital or estimate their current health state. Given the low accuracy of systolic pressure measurement, it is recommended to develop an algorithm that will allow smooth measuring error for higher-precision estimation of the patient`s general health state. In addition, it is planned to improve the positioning algorithm.

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Low-Power Indoor Positioning Algorithm Based on iBeacon Network

Complexity ◽

10.1155/2021/8475339 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Xiaona Zhang ◽

Shufang Zhang ◽

Shuaiheng Huai

Keyword(s):

Low Power ◽

Performance Improvement ◽

General Framework ◽

Logical Structure ◽

Indoor Positioning ◽

Positioning System ◽

Depth Analysis ◽

Communication Distance ◽

Positioning Algorithm ◽

Indoor Positioning System

In this article, we use a low-power iBeacon network to conduct an in-depth analysis and research on the principle of indoor positioning and adopt an efficient and fast positioning algorithm. Secondly, based on the obtained analysis, an iBeacon-based indoor positioning system is proposed to analyze how to use iBeacon for accurate positioning and whether it can effectively compensate for the current mainstream positioning system. We analyze the requirements of the iBeacon-based indoor positioning system and propose the design of this positioning system. We analyze the platform and environment for software development, design the general framework of the positioning system, and analyze the logical structure of the whole system, the structure of data flow, and the communication protocols between each module of the positioning system. Then, we analyze the functions of the server module and the client module of the system, implement the functions of each module separately, and debug the functions of each module separately after each module is implemented. The feasibility of the algorithm and the performance improvement are confirmed by the experimental data. Our results show that the communication distance is improved by approximately 20.25% and the accuracy is improved by 5.62% compared to other existing results.

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Mobile Robot Indoor Positioning System Based on K-ELM

Journal of Sensors ◽

10.1155/2019/7547648 ◽

2019 ◽

Vol 2019 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Haixia Wang ◽

Junliang Li ◽

Wei Cui ◽

Xiao Lu ◽

Zhiguo Zhang ◽

...

Keyword(s):

Mobile Robot ◽

Indoor Localization ◽

Indoor Positioning ◽

Positioning System ◽

Positioning Accuracy ◽

Positioning Method ◽

Kernel Extreme Learning Machine ◽

Learning Machine ◽

Positioning Algorithm ◽

Indoor Positioning System

Mobile Robot Indoor Positioning System has wide application in the industry and home automation field. Unfortunately, existing mobile robot indoor positioning methods often suffer from poor positioning accuracy, system instability, and need for extra installation efforts. In this paper, we propose a novel positioning system which applies the centralized positioning method into the mobile robot, in which real-time positioning is achieved via interactions between ARM and computer. We apply the Kernel extreme learning machine (K-ELM) algorithm as our positioning algorithm after comparing four different algorithms in simulation experiments. Real-world indoor localization experiments are conducted, and the results demonstrate that the proposed system can not only improve positioning accuracy but also greatly reduce the installation efforts since our system solely relies on Wi-Fi devices.

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Novel Model of Wireless Sensor with Indoor Positioning Algorithm and Time Synchronization Protocol

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1046.335 ◽

2014 ◽

Vol 1046 ◽

pp. 335-338

Author(s):

Qiu Hong Zhang ◽

Liang Jin

Keyword(s):

Network Structure ◽

Time Synchronization ◽

Indoor Positioning ◽

Wireless Sensor ◽

Positioning System ◽

Head Node ◽

Positioning Algorithm ◽

Indoor Positioning System ◽

Novel Model ◽

Synchronization Protocol

This paper describes the positioning based on ZigBee network, and it provides location indoor information and node state alarm information. Wireless sensor indoor positioning system consists of 3 types nodes: the coordinator node, reference node and blind. Time synchronization protocol is an efficient synchronization technology star network structure, synchronization to the gateway node as a starting point, each cluster head node synchronization tree network structure. The paper presents novel model of wireless sensor indoor positioning algorithm and time synchronization protocol. Experiments show that the design of indoor positioning system can meet requirement function and performance of nodes positioning system.

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EVALUATION OF DYNAMIC AD-HOC UWB INDOOR POSITIONING SYSTEM

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-1-379-2018 ◽

2018 ◽

Vol XLII-1 ◽

pp. 379-385 ◽

Cited By ~ 1

Author(s):

M. Sakr ◽

A. Masiero ◽

N. El-Sheimy

Keyword(s):

Ad Hoc ◽

Indoor Positioning ◽

Position Estimation ◽

Ultra Wideband ◽

Positioning System ◽

Range Measurements ◽

Precision Time ◽

Anchor Points ◽

Positioning Algorithm ◽

Indoor Positioning System

Abstract. Ultra-wideband (UWB) technology has witnessed tremendous development and advancement in the past few years. Currently available UWB transceivers can provide high-precision time-of-flight measurements which corresponds to range measurements with theoretical accuracy of few centimetres. Position estimation using range measurement is determined by measuring the ranges from a rover or a dynamic node, to a set of anchor points with known positions. However, building a flexible and accurate indoor positioning system requires more than just accurate range measurements. The performance of indoor positioning system is affected by the number and the configuration of the anchor points used, along with the accuracy of the anchor positions.This paper introduces LocSpeck, a dynamic ad-hoc positioning system based on the DW1000 UWB transceiver from Decawave. LocSpeck is composed of a set of identical nodes communicating on a common RF channel, forming a fully or partially connected network where the positioning algorithm run on each node. Each LocSpeck node could act as an anchor or a rover, and the role could change dynamically during the same session. The number of nodes in the network could change dynamically, since the firmware of LocSpeck supports adding and removing nodes on-the-fly. The paper compares the performance of the LocSpeck system with commercially available off-the-shelf UWB positioning system. Different operating scenarios are considered when evaluating the performance of the system, including cases where collaboration between the two systems is considered.

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