Application of Improved LANDMARC Indoor Positioning Algorithm in Neurology Medical Care Monitoring and Positioning System

Huang, Yanzhu; Li, Ling; Hu, Luhong; Huang, Hong; Liao, Zongfeng; Wang, Junjing

doi:10.1016/j.wneu.2020.01.172

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…In the two-dimensional plane, at least three known position points are required as reference points, and these three known reference points are used as the center point, and the distance between the LED and PD obtained under the above received signal strength RSS attenuation is used as a half diameter to draw an arc; then the intersection of the three arcs is the estimated position of the target unknown point [ 31 ]. As shown in Figure 5 , points A, B, and C are the positions of the three LED lights, X are the coordinate positions of the moving target points., According to the received signal strength, RSS measures the distance between the three LEDs and the PD, respectively is the sum of squares of d 1 , d 2 and d 3 so that the intersection of the three circles is ideally the moving target position [ 11 ].…”

Section: Visible Light Positioning Methods and Common Positioning Alg...mentioning

confidence: 99%

Research and Implementation of Indoor 3D Positioning Algorithm Based on LED Visible Light Communication and Corresponding Parameter Estimation

2022

Computational Intelligence and Neuroscience

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In the era of mobile Internet, the application of various positioning-based location service systems is becoming more and more common. In addition, the traditional radio positioning system is limited in the use of special environments such as mines, hospitals, and gas stations, and long-term electromagnetic radiation can cause potential damage to the human body. Compared with the traditional wireless positioning technology, VLC-based positioning technology has a good application prospect in the field of indoor wireless positioning. Compared with traditional radio positioning technology, the use of VLC technology to achieve indoor positioning is different in that the system design and layout need to consider the basic needs of indoor lighting; that is, the layout of multiple visible light sources in the room should meet the minimum illumination requirements of any area of the room. Since the layout structure of the light source that only considers the lighting requirements or only considers the positioning accuracy requirements is not the same, in the design process of the indoor visible light wireless positioning system, it is necessary to consider the overall optimization layout of multiple indoor visible light sources under the conditions of lighting and positioning constraints. This paper mainly optimizes indoor positioning from the aspects of light source layout, reflected light intensity distribution, and noise model.

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Section: Visible Light Positioning Methods and Common Positioning Alg...mentioning

confidence: 99%

Research and Implementation of Indoor 3D Positioning Algorithm Based on LED Visible Light Communication and Corresponding Parameter Estimation

2022

Computational Intelligence and Neuroscience

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“…Works [19,20,39] describe IPS based on RFID for monitoring elderly people at home. It is worthwhile noting that the IPS described in [39] also combines inertial sensors (like gyroscope and accelerometer).…”

Section: Hong Et Al In Their Papermentioning

confidence: 99%

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

et al. 2021

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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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“…In recent years, indoor localization-based services have played a significant role in many fields, including monitoring and security services, visualization and traceability of industrial assembly lines, underground engineering operations, mall localization, and advertising push. Enhancing the accuracy of localization technology can raise the quality of service [1].…”

Section: Introductionmentioning

confidence: 99%

Wi-Fi indoor 3D localization algorithm based on multi-classifier fusion

Wu¹,

Zhang²,

Yang³

et al. 2022

Eng. Res. Express

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Indoor localization technology based on Received Signal Strength (RSS) fingerprint is widely used in life and industry. Compared with the traditional localization methods, the localization technology integrating multiple machine learning methods has better localization accuracy. However, in multi-floor localization, the existing fusion localization technology ignores the interaction between different floors in the localization process, resulting in low indoor localization accuracy. This paper proposes a Wi-Fi indoor 3D localization method based on multi-classifier fusion named FLMCF. Firstly, floor classification training is carried out to reduce the location deviation in the vertical direction. Secondly, for each floor, multiple classifiers are used for model training and training the optimal weight set by minimizing the average localization error. In this case, the advantages of each classifier can be fully integrated to improve the localization accuracy. Finally, the Reliability Fusion Weight Selection (RFWS) algorithm determines the weight and calculates the final location estimation. The experimental results indicate that FLMCF is nearly 14.1% better than DIFMIC in the 90th percentile of CDF.

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Application of Improved LANDMARC Indoor Positioning Algorithm in Neurology Medical Care Monitoring and Positioning System

Cited by 7 publications

References 10 publications

Research and Implementation of Indoor 3D Positioning Algorithm Based on LED Visible Light Communication and Corresponding Parameter Estimation

Research and Implementation of Indoor 3D Positioning Algorithm Based on LED Visible Light Communication and Corresponding Parameter Estimation

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

Wi-Fi indoor 3D localization algorithm based on multi-classifier fusion

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