Design of Beacon-Based Positioning System Using RF and Sound Wave in Smartphone

Lee, Hyun-Seong; Lee, Seoung-Hyeon; Lee, Jae-Gwang; Lee, Jae-Kwang

doi:10.1007/978-981-10-7605-3_30

Cited by 3 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Kawai et al [15] An enhanced Kalman filter-based multilayer perceptron (MLP) was presented to process BLE RSSI data. Lee et al [16] proposed a new technique where signals at a specific frequency were sent by Waveguide, it included RF and audio signals. Distance and trilateration are determined using the TDOA method, and they concluded that TDOA method is more reliable than other methods like AOA.…”

Section: Literature Surveymentioning

confidence: 99%

“…Considering the measuring distances as (ai, bi) represents to x and y coordinate with difference matrix (12), the equation can be rewritten as 13, (13) With the error verification equation 14 written for the ith coordinate as (14) From the above matrix, the equation 15 written for for sensor coordinate as (15) The diagonal distance transpose matrix for sensor to node location written in the equation 16 as (16).…”

Section: K= ( ) (5)mentioning

confidence: 99%

See 1 more Smart Citation

Improved Chan Algorithm Based Optimum UWB Sensor Node Localization Using Hybrid Particle Swarm Optimization

et al. 2022

View full text Add to dashboard Cite

The localization of Wireless sensor networks (WSNs) has been recognized as one of the most challenging problems to overcome. Thus, much work has been given to solving this difficult problem. In emergency services, navigational systems, civil/military surveillance etc., locating the signal source in a WSN is essential. A novel approach for sensor node localization using range-based localization methodology has been proposed to overcome this issue. The problem is expressed in the form of a maximum probability distribution function. The use of an RSSI-based Time Difference of Arrival (TDOA) measurement model, along with the Chan algorithm, is used to find the coordinates of unknown nodes has been proposed. With the help of ultra-wideband, this research aims to develop new and precise localization algorithms for wireless sensor networks (WSNs). This work offers localization using two-hybrid localization algorithms, i.e., ELPSO (Ensemble learning particle swarm optimization) and PSO-BPNN (Back-propagation neural network optimized by particle swarm optimization). Further, the error optimization accuracy has been compared between those algorithms using simulations. The proposed techniques consistently offer a better localization accuracy than the conventional algorithms available in the literature. The new localization methods with optimal techniques reduce the error value to a minimal distance. The distance value of localization error is nearly2.7cms compared to other designs from the literature. It is noted as significantly less.

show abstract

Section: Literature Surveymentioning

confidence: 99%

Section: K= ( ) (5)mentioning

confidence: 99%

Improved Chan Algorithm Based Optimum UWB Sensor Node Localization Using Hybrid Particle Swarm Optimization

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Other techniques for object detection in an indoor positioning environment rely on reference from 3D building models, that depend on detecting objects in images and then matching these with a built database, i.e., CityGML contains position data of the interior of building. These methods have advantageous, as there is no need to deploy sensor beacons [30,31]. In this regard, important research has been conducted by Kohoutek et al [10], using CityGML as highest level of detail for determining position of imagining camera within the range.…”

Section: Related Studymentioning

confidence: 99%

Autonomous Smart White Cane Navigation System for Indoor Usage

2020

View full text Add to dashboard Cite

According to the statistics provided by the World Health Organization, the number of people suffering from visual impairment is approximately 1.3 billion. The number of blind and visually impaired people is expected to increase over the coming years, and it is estimated to triple by the end of 2050 which is quite alarming. Keeping the needs and problems faced by the visually impaired people in mind, we have come up with a technological solution that is a “Smart Cane device” that can help people having sight impairment to navigate with ease and to avoid the risk factors surrounding them. Currently, the three main options available for blind people are using a white cane, technological tools and guide dogs. The solution that has been proposed in this article is using various technological tools to come up with a smart solution to the problem to facilitate the users’ life. The designed system mainly aims to facilitate indoor navigation using cloud computing and Internet of things (IoT) wireless scanners. The goal of developing the Smart Cane can be achieved by integrating various hardware and software systems. The proposed solution of a Smart Cane device aims to provide smooth displacement for the visually impaired people from one place to another and to provide them with a tool that can help them to communicate with their surrounding environment.

show abstract

“…Huh and Seo [10] used Bluetooth 4.0, received signal strength indication (RSSI), Bluetooth Low Energy (BLE), and trilateration to determine the position of the user in an indoor space. Kawai et al [11] used BLE RSSI data processed by multilayer perceptron (MLP) with an extended Kalman filter, reaching an error of 2.21 m. Lee et al [12] used Beacon to transmit a radio frequency (RF) signal and an audio signal of specific frequency. The smartphone calculates distance values using the Time Difference of Arrival (TDoA) method and uses them for trilateration.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings

Almadani

Orujov

Maskeliūnas

et al. 2019

Sensors

View full text Add to dashboard Cite

The ability to precisely locate and navigate a partially impaired or a blind person within a building is increasingly important for a wide variety of public safety and localization services. In this paper, we explore indoor localization algorithms using Bluetooth Low Energy (BLE) beacons. We propose using the BLE beacon’s received signal strength indication (RSSI) and the geometric distance from the current beacon to the fingerprint point in the framework of fuzzy logic for calculating the Euclidean distance for the subsequent determination of location. According to our results, the fingerprinting algorithm with fuzzy logic type-2 (hesitant fuzzy sets) is fit for use as an indoor localization method with BLE beacons. The average error of localization is only 0.43 m, and the algorithm obtains a navigation precision of 98.2 ± 1%. This precision confirms that the algorithms provide great aid to a visually impaired person in unknown spaces, especially those designed without physical tactile guides, as confirmed by low Fréchet and Hausdorff distance values and high navigation efficiency index (NEI) scores.

show abstract

Design of Beacon-Based Positioning System Using RF and Sound Wave in Smartphone

Cited by 3 publications

References 5 publications

Improved Chan Algorithm Based Optimum UWB Sensor Node Localization Using Hybrid Particle Swarm Optimization

Improved Chan Algorithm Based Optimum UWB Sensor Node Localization Using Hybrid Particle Swarm Optimization

Autonomous Smart White Cane Navigation System for Indoor Usage

Fuzzy Logic Type-2 Based Wireless Indoor Localization System for Navigation of Visually Impaired People in Buildings

Contact Info

Product

Resources

About