Developing a Novel Real-Time Indoor Positioning System Based on BLE Beacons and Smartphone Sensors

Dinh, Thai-Mai Thi; Duong, Ngoc-Son; Nguyen, Quoc-Tuan

doi:10.1109/jsen.2021.3106019

Cited by 29 publications

(10 citation statements)

References 30 publications

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“…The mobile device transmits a signal to many stationary access points, combined using a Center of Gravity method to determine where the consumer is. Dinh et al discuss using beacons equipped with Bluetooth for geographical monitoring [11]. Bluetooth is widely used in many devices, such as wearables and phones.…”

Section: Background and Literature Surveymentioning

confidence: 99%

IoT-based centralized wireless patient tracking and surveillance system with a cutting-edge approach for advanced healthcare oversight and data-driven analysis

Ganesh,

Gangopadhyay,

Kumar Lingamallu

et al. 2024

MATEC Web Conf.

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The construction of smart cities has been progressing quickly due to advancements in 5G and Internet of Things (IoT) technology. Smart transportation systems and smart medical ideas are also being explored alongside smart city initiatives. Integrating the two mentioned technologies, a smart navigational method for ambulances is being developed. When severe patients arrive via ambulance, significant time is wasted in relaying data, and the hospital needs to gain prior knowledge of the patient's condition. An efficient system called the IoT-based Wireless Patient Tracking Method (IoT-WPTM) is proposed to diagnose patients quickly by recording vital metrics such as heartbeat, temperature, and breathing rate using detectors. These variables are transmitted wirelessly to the healthcare before the ambulance is dispatched, allowing doctors to begin medical care promptly. If necessary, the patient monitors the ambulance's position to anticipate arrival and get immediate directions to the closest hospital. The user carries the gadget and is also placed in the ambulance. The gadget allows IoT devices and Android apps to enhance user interaction and streamline information delivery. IoT-WPTM can be surpassed with ease and in a more effective manner for smart medical surveillance systems.

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Section: Background and Literature Surveymentioning

confidence: 99%

IoT-based centralized wireless patient tracking and surveillance system with a cutting-edge approach for advanced healthcare oversight and data-driven analysis

Ganesh,

Gangopadhyay,

Kumar Lingamallu

et al. 2024

MATEC Web Conf.

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“…t swing = 0.5 × (t swing acc + t swing gyro ), (1) where t swing acc and t swing gyro denote the duration of swing phase calculated from acceleration signal and angular velocity signal respectively. The peak-valley detection method adopted here is based on normalized threshold value and minimum time interval between the consecutive peak or valley points as provided in [39]. Normalized threshold constraint [40], at first is used to select all maxima (i.e., peak) points as well as minima (i.e., valley) points from the Z-axis acceleration signal.…”

Section: Calculation Of Swing Phase Durationmentioning

confidence: 99%

Human Gait Modeling with Step Length Estimation based on Single Foot Mounted Inertial Sensors

Gayen

Sadhukhan

Chowdhury

et al. 2023

Preprint

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The rapid growth of mobile communication and pervasive computing technology has expanded the demand for location-based services in urban areas, which necessitate accurate localization and tracking of the user. Due to very poor performances of global positioning system (GPS) in indoor areas and urban canyons, various radio frequency (RF) technologies have been exploited by many researchers to design indoor positioning systems (IPSs) over the years. However, such RF based IPSs would work only in the presence of certain infrastructure. The emergence of low-cost inertial sensors like accelerometer, gyroscope etc., on the other hand, has motivated the researchers to design pedestrian dead reckoning (PDR) based IPSs as they do not depend on availability of any sort of infrastructure in the surrounding environment. Step length estimation (SLE) is an integral part of PDR based localization. We, thus, aim to design a SLE technique in this paper, by processing signal measurements collected from the inertial sensors attached to some body parts. Our proposed SLE method requires only a simple foot-mounted inertial sensor unit integrating three-axis accelerometer and gyroscope and it uses Butterworth low-pass filter to remove the noises from both acceleration and angular velocity signals. A normalized threshold and minimum time constraint-based peak-valley detection algorithm is also employed by our proposed method to calculate the swing phase duration. The proposed SLE technique uses only one user-specific parameter which is also calibrated for five different users in this paper. The performances of the proposed SLE technique are then evaluated and compared with some existing method in terms of accuracy to demonstrate the efficacy of the proposed method. Moreover, the relationships between the gait features and step length of the pedestrians as well as the same between their body mass index and the calibrated parameter are also examined in this paper.

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“…In Dinh et al, 49 Thai‐Mai Thi Dinh et al study the problem of PDR positioning system and RSS‐based position measurement. Then, they propose a real‐time and highly accurate positioning system using BLE iBeacons.…”

Section: Related Workmentioning

confidence: 99%

THIP: A trajectory history‐based indoor positioning algorithm using stress‐free floor plan for patient monitoring

Jalali

Kheirabadi

2023

Int J Communication

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Summary The Internet of Things (IoT) is a novel paradigm that consists of a wide network of machines and intelligent devices with the capability of communication and interaction with each other. One of the significant issues for the IoT is its healthcare applications. The positioning systems based on their environment can be classified into two main categories: Indoor and outdoor. Recently, IoT indoor positioning attracts too much attention among researchers for patient monitoring. Hence, in this paper, a stress‐free floor plan indoor positioning algorithm for patient monitoring is proposed, called THIP. The history of the patient's movement is stored in a trajectory history, and this information is employed to estimate the patient's more accurate position. The proposed THIP algorithm is simulated in MATLAB software. Several experiments are conducted to evaluate the performance of the proposed algorithm. Simulation results show that the proposed THIP algorithm raises patient positioning accuracy and declines the distance error cumulative compared to LiFS by about 4.68% and 60.6 m, respectively. Moreover, it can identify the floor level of the moving user.

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Developing a Novel Real-Time Indoor Positioning System Based on BLE Beacons and Smartphone Sensors

Cited by 29 publications

References 30 publications

IoT-based centralized wireless patient tracking and surveillance system with a cutting-edge approach for advanced healthcare oversight and data-driven analysis

IoT-based centralized wireless patient tracking and surveillance system with a cutting-edge approach for advanced healthcare oversight and data-driven analysis

Human Gait Modeling with Step Length Estimation based on Single Foot Mounted Inertial Sensors

THIP: A trajectory history‐based indoor positioning algorithm using stress‐free floor plan for patient monitoring

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