An Indoor Positioning Approach Based on Fusion of Cameras and Infrared Sensors

Martín-Gorostiza, Ernesto; García-Garrido, Miguel Ángel; Pizarro, Daniel; Salido-Monzú, David; Torres, Patricia García

doi:10.3390/s19112519

Cited by 19 publications

(6 citation statements)

References 51 publications

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“…This study introduces a mine-pressure-monitoring-oriented working-face footage automatic-acquisition system, selecting the SDS-TWR ranging algorithm and three-side positioning algorithm suitable for the underground environment of coal mines to obtain the working-face footage information and, at the same time, combine with mining pressure sensors to monitor the pressure of the hydraulic stent of the synthesized mining face to realize the dynamic monitoring of the working face, as well as plotting the distribution matrix of the stent resistance at the working face to monitor the location of the local incoming pressure and calculate the incoming pressure step distance. The UWB [14][15][16] has the characteristic of narrowband pulsed communication without the need for a carrier. The Federal Communications Commission (FCC) defines UWB signaling as shown below:…”

Section: Introductionmentioning

confidence: 99%

Automatic Acquisition System for Mine Pressure Monitoring in Coal Mine Working-Face Footage

Zhou,

Shi,

Hao

et al. 2024

Journal of Sensors

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The existing mine pressure monitoring system has realized the online continuous monitoring of the working-face stent resistance, roadway roof offcuts, and anchor rod/rope working resistance. However, the mine pressure monitoring information of the working face currently includes only the stent resistance and the monitoring time, and there is no information on the working-face advance. The mine pressure data cannot be precisely analyzed due to a lack of measurement point locations. Mine pressure data analysis combined with the working-face feed information is the basis for safe and efficient mining and for improving the intelligence level of the comprehensive mining face. According to the special electromagnetic environment of the underground, this system adopts UWB (ultra-wide-band) technology and the SDS-TWR (symmetric double-sided two-way ranging) ranging method, with the UWB positioning base station as the core and installs positioning tags at the end supports of the working face to collect information. The data are uploaded to the host computer via Ethernet for coordinate solving, automatically collecting the working-face footage data and providing positional information for mine pressure monitoring. The application results show that the system operates normally and can collect real-time information of working-face footage and monitor mine pressure data, and meet the requirements of coal mine positioning accuracy, positioning error is less than 30 cm, the application effect is good.

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Section: Introductionmentioning

confidence: 99%

Automatic Acquisition System for Mine Pressure Monitoring in Coal Mine Working-Face Footage

Zhou,

Shi,

Hao

et al. 2024

Journal of Sensors

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“…Although these methods have high recognition accuracy, they have great limitations in the more common multipath environment. For example, infrared technology [ 1 ] is usually used in indoor spaces with few multipath paths. When people pass, they will trigger the corresponding alarm.…”

Section: Introductionmentioning

confidence: 99%

Capturing Features and Performing Human Detection from Human Gaits Using RFID

Zhang

Liu

Yang

et al. 2022

Sensors

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Recently, radio frequency identification (RFID) sensing has attracted much attention due to its contact-free nature, low cost, light weight and other advantages. RFID-based person detection has also become a hot research topic, but there are still some problems in the existing research. First, most of the current studies cannot identify numerous people at a time well. Second, in order to detect more accurately, it is necessary to evaluate the whole-body activity of a person, which will consume a lot of time to process the data and cannot be applied in time. To solve these problems, in this paper we propose RF-Detection, a person detection system using RFID. First of all, RF-Detection takes step length as the standard for person detection, divides step length into specific sections according to the relationship between step length and height, and achieves high accuracy for new user detection through a large amount of training for a specific step length. Secondly, RF-Detection can better identify the number of people in the same space by segmenting continuous people. Finally, the data collection was reduced by expanding the data set, and the deep learning method was used to further improve the accuracy. The results show that the overall recognition accuracy of RF-Detection is 98.93%.

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“…Some of them require a costly, heavy and pre-installed infrastructure to work (e.g., Wireless Local Area Network (WLAN) [ 5 ], Radio Frequency Identification (RFID) [ 6 ], etc.). Others rely on more traditional methods, such as computer vision techniques [ 7 ], which can be inaccessible in certain situations (smoke in building for instance). The most common solution to the case where the conditions of intervention, and the availability of pre-installed equipment are unknown, is the use of low-cost Inertial Measurement Units (IMUs), composed of inertial and magnetic sensors.…”

Section: Introductionmentioning

confidence: 99%

Magnetic Field Gradient-Based EKF for Velocity Estimation in Indoor Navigation

Zmitri

Fourati

Prieur

2020

Sensors

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This paper proposes an advanced solution to improve the inertial velocity estimation of a rigid body, for indoor navigation, through implementing a magnetic field gradient-based Extended Kalman Filter (EKF). The proposed estimation scheme considers a set of data from a triad of inertial sensors (accelerometer and gyroscope), as well as a determined arrangement of magnetometers array. The inputs for the estimation scheme are the spatial derivatives of the magnetic field, from the magnetometers array, and the attitude, from the inertial sensors. As shown in the literature, there is a strong relation between the velocity and the measured magnetic field gradient. However, the latter usually suffers from high noises. Then, the novelty of the proposed EKF is to develop a specific equation to describe the dynamics of the magnetic field gradient. This contribution helps to filter, first, the magnetic field and its gradient and second, to better estimate the inertial velocity. Some numerical simulations that are based on an open source database show the targeted improvements. At the end of the paper, this approach is extended to position estimation in the case of a foot-mounted application and the results are very promising.

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An Indoor Positioning Approach Based on Fusion of Cameras and Infrared Sensors

Cited by 19 publications

References 51 publications

Automatic Acquisition System for Mine Pressure Monitoring in Coal Mine Working-Face Footage

Automatic Acquisition System for Mine Pressure Monitoring in Coal Mine Working-Face Footage

Capturing Features and Performing Human Detection from Human Gaits Using RFID

Magnetic Field Gradient-Based EKF for Velocity Estimation in Indoor Navigation

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