scholarly journals THE GLOBAL OPTIMAL PLACEMENT OF BLE BEACON FOR LOCALIZATION BASED ON INDOOR MAP

2018 ◽  
Vol XLII-4 ◽  
pp. 529-534
Author(s):  
L. Ruan ◽  
L. Zhang ◽  
F. Cheng ◽  
Y. Long
Keyword(s):  
Indoor Positioning ◽  
Optimal Placement ◽  
Prototype System ◽  
Localization Accuracy ◽  
Space Objects ◽  
Positioning Method ◽  
Anchor Nodes ◽  
Global Optimal ◽  
The Cost ◽  
Indoor Positioning System

<p><strong>Abstract.</strong> Anchor Nodes in a localization system obviously play a crucial role in determining the system’s quality. Their placement directly affects the localization accuracy and their number directly impacts the total cost of the system. Nowadays, the deployment of Bluetooth nodes in industry generally relies on the experience knowledge of engineers and the cost of positioning beacon does not considered the global level. In this paper, we put forward a method to extract the number and location of BLE beacon automatically and ensure a high positioning accuracy of the indoor positioning system based the rules of indoor positioning, which use all kinds of space objects and structure characteristics of indoor map. The triangulation method was selected to study the global optimal placement of BLE beacon for localization based on indoor map. The impacts and requirements of BLE beacon placement were systematic analysed from the triangulation positioning method, indoor positioning environment and indoor user distribution characteristics. According to the characteristics of indoor environment structure and user distribution, we built an optimization model of BLE beacon placement method based on genetic algorithm which can generate the number and the location of BLE beacon. At last, the Bluetooth indoor positioning prototype system is developed to compare the experience method deployment scheme and the global optimization deployment scheme in the real indoor positioning environment.</p>

scholarly journals An Indoor Positioning System Using Multiple Methods and Tools

2018 ◽  
Vol 4 (1) ◽  
pp. 11-22
Author(s):  
Michael Adeyeye Oshin ◽  
Nobaene Sehloho
Keyword(s):  
Wireless Mesh Network ◽  
Ad Hoc ◽  
Indoor Positioning ◽  
Mesh Network ◽  
Positioning System ◽  
Tracking Systems ◽  
Positioning Systems ◽  
Wireless Mesh ◽  
Positioning Method ◽  
Indoor Positioning System

With many different studies showing a growing demand for the development of indoor positioning systems, numerous positioning and tracking methods and tools are available for which can be used for mobile devices. Therefore, an interest is more on development of indoor positioning and tracking systems that are accurate and effective. Presented and proposed in this work, is an indoor positioning system. As opposed to an Ad-hoc Positioning System (APS), it uses a Wireless Mesh Network (WMN). The system makes use of an already existing Wi-Fi infrastructure technology. Moreover, the approach tests the positioning of a node with its neighbours in a mesh network using multi-hopping functionality. The positioning measurements used were the ICMP echos, RSSI and RTS/CTS requests and responses. The positioning method used was the trilateral technique, in combination with the idea of the fingerprinting method. Through research and experimentation, this study developed a system which shows potential as a positioning system with an error of about 2 m to 3 m. The hybridisation of the method proves an enhancement in the system though improvements are still required.

scholarly journals Indoor Localization System Using Wireless Sensor Network

2018 ◽  
pp. 29-38
Keyword(s):  
Indoor Localization ◽  
Low Cost ◽  
Wide Band ◽  
Human Movement ◽  
Indoor Positioning ◽  
Positioning System ◽  
Wireless System ◽  
Anchor Nodes ◽  
Indoor Positioning System ◽  
Better Than

Building a precise low cost indoor positioning and navigation wireless system is a challenging task. The accuracy and cost should be taken together into account. Especially, when we need a system to be built in a harsh environment. In recent years, several researches have been implemented to build different indoor positioning system (IPS) types for human movement using wireless commercial sensors. The aim of this paper is to prove that it is not always the case that having a larger number of anchor nodes will increase the accuracy. Two and three anchor nodes of ultra-wide band with or without the commercial devices (DW 1000) could be implemented in this work to find the Localization of objects in different indoor positioning system, for which the results showed that sometimes three anchor nodes are better than two and vice versa. It depends on how to install the anchor nodes in an appropriate scenario that may allow utilizing a smaller number of anchors while maintaining the required accuracy and cost.

scholarly journals Indoor Positioning Method Based on Wireless Signal

2018 ◽  
Vol 14 (10) ◽  
pp. 53
Author(s):  
Jingjing Yang ◽  
Zhenyu Feng ◽  
Xuchao Ma ◽  
Xiao Zhang
Keyword(s):  
Measurement Accuracy ◽  
Wave Attenuation ◽  
Indoor Positioning ◽  
Least Square ◽  
Font Size ◽  
Least Square Fitting ◽  
Fitting Algorithm ◽  
Wireless Signal ◽  
Positioning Method ◽  
Indoor Positioning System

<span style="font-family: 'Times New Roman',serif; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: DE; mso-ansi-language: EN-US; mso-bidi-language: AR-SA;">In view of the problems of traditional wireless indoor positioning technologies such as errors and a low positioning accuracy that cannot reach the application level required by hospital indoor positioning, this study proposes a hospital indoor positioning method based on wireless signals. This study firstly analyzes the principles of hospital indoor positioning, verifies the reliability and accuracy of the collected data using Gaussian distribution, P-P plot and Q-Q plot, and finally analyzes the collected data using the least square fitting algorithm to obtain a fitting wave attenuation model, which is then applied to the indoor positioning system. Experiments show that this method can reduce the error of indoor positioning in hospitals, and improve the repeatability and measurement accuracy of indoor positioning in hospitals.</span>

scholarly journals Mobile Robot Indoor Positioning System Based on K-ELM

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
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.

scholarly journals Platform and Algorithm Development for a RFID-Based Indoor Positioning System

2014 ◽  
Vol 02 (03) ◽  
pp. 279-291 ◽  
Author(s):  
Han Zou ◽  
Lihua Xie ◽  
Qing-Shan Jia ◽  
Hengtao Wang
Keyword(s):  
Radio Frequency Identification ◽  
Indoor Positioning ◽  
Location Estimation ◽  
Support Vector ◽  
Rfid Tags ◽  
Positioning System ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Reference Tags ◽  
Indoor Positioning System

In recent years, developing Indoor Positioning System (IPS) has become an attractive research topic due to the increasing demands on Location-Based Service (LBS) in indoor environment. Several advantages of Radio Frequency Identification (RFID) Technology, such as anti-interference, small, light and portable size of RFID tags, and its unique identification of different objects, make it superior to other wireless communication technologies for indoor positioning. However, certain drawbacks of existing RFID-based IPSs, such as high cost of RFID readers and active tags, as well as heavy dependence on the density of reference tags to provide the LBS, largely limit the application of RFID-based IPS. In order to overcome these drawbacks, we develop a cost-efficient RFID-based IPS by using cheaper active RFID tags and sensors. Furthermore, we also proposed three localization algorithms: Weighted Path Loss (WPL), Extreme Learning Machine (ELM) and integrated WPL-ELM. WPL is a centralized model-based approach which does not require any reference tags and provides accurate location estimation of the target effectively. ELM is a machine learning fingerprinting-based localization algorithm which can provide higher localization accuracy than other existing fingerprinting-based approaches. The integrated WPL-ELM approach combines the fast estimation of WPL and the high localization accuracy of ELM. Based on the experimental results, this integrated approach provides a higher localization efficiency and accuracy than existing approaches, e.g., the LANDMARC approach and the support vector machine for regression (SVR) approach.

scholarly journals A Survey of Smartphone-Based Indoor Positioning System Using RF-Based Wireless Technologies

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7230
Author(s):  
Santosh Subedi ◽  
Jae-Young Pyun
Keyword(s):  
Indoor Localization ◽  
Indoor Positioning ◽  
Performance Comparison ◽  
Location Based Services ◽  
Global Navigation Satellite Systems ◽  
Smart Devices ◽  
Positioning System ◽  
Localization Accuracy ◽  
Satellite Systems ◽  
Indoor Positioning System

In recent times, social and commercial interests in location-based services (LBS) are significantly increasing due to the rise in smart devices and technologies. The global navigation satellite systems (GNSS) have long been employed for LBS to navigate and determine accurate and reliable location information in outdoor environments. However, the GNSS signals are too weak to penetrate buildings and unable to provide reliable indoor LBS. Hence, GNSS’s incompetence in the indoor environment invites extensive research and development of an indoor positioning system (IPS). Various technologies and techniques have been studied for IPS development. This paper provides an overview of the available smartphone-based indoor localization solutions that rely on radio frequency technologies. As fingerprinting localization is mostly accepted for IPS development owing to its good localization accuracy, we discuss fingerprinting localization in detail. In particular, our analysis is more focused on practical IPS that are realized using a smartphone and Wi-Fi/Bluetooth Low Energy (BLE) as a signal source. Furthermore, we elaborate on the challenges of practical IPS, the available solutions and comprehensive performance comparison, and present some future trends in IPS development.

scholarly journals INTEGRATION OF PDR AND IMAGE-BASED POSITIONING AIDED BY ARTIFICIAL NEURAL NETWORKS IN INDOOR ENVIRONMENT

2020 ◽  
Vol XLIII-B1-2020 ◽  
pp. 181-185
Author(s):  
M. C. Hung ◽  
K. W. Chiang
Keyword(s):  
Dead Reckoning ◽  
Satellite System ◽  
Indoor Positioning ◽  
Indoor Navigation ◽  
Positioning Method ◽  
Pros And Cons ◽  
Positioning Technique ◽  
The Mean ◽  
Global Navigation Satellite ◽  
The Cost

Abstract. Location based service (LBS) is a popular issue in recent years, which can be applied widely. The most common one is providing the local information and the guide of the Point of Interesting (POI) to users, which means positioning is the necessary technique to put LBS into practice. In an outdoor scenario, the user’s position can be obtained relying on the Global Navigation Satellite System (GNSS), however, the signal of GNSS might be blocked in a building. So, many indoor positioning techniques are developed in the decades, which have the pros and cons respectively. This paper proposes an indoor positioning technique by integrating Pedestrian Dead Reckoning (PDR) with the image-based positioning method, which can decrease the cost significantly because it only needs a camera built-in the smartphone. In the first experiment, we verify the accuracy of positioning by the proposed method, that the mean error in the horizontal direction is about 0.25 meters. In the following experiment, comparing with the misclosure of PDR only and PDR integrated with the proposed method, it can decrease from 8.53% to 1.44%. The improvement is about 83%, therefore, this method is suitable for applying to indoor navigation.

scholarly journals A Context-Aware Assisted WiFi Positioning Method

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qi Feng ◽  
Bing Jia ◽  
Xi Luo ◽  
Sha Li
Keyword(s):  
Indoor Positioning ◽  
Identification Algorithm ◽  
Context Aware ◽  
Limited Information ◽  
Location Based Service ◽  
Positioning Accuracy ◽  
Localization Accuracy ◽  
Variable Weight ◽  
Positioning Method ◽  
Weight Dynamic

With the convenience brought by Location-based service (LBS), users’ requirements for indoor positioning accuracy are getting higher than ever. However, many traditional indoor WiFi positioning methods may result in limited positioning accuracy because of the limited information of Received Signal Strength (RSS) of WiFi signal. This paper proposed a context-aware assisted WiFi positioning method (CAA-PM), which uses context information (i.e., light and sound) to assist WiFi-RSS for indoor positioning and uses an improved variable weight dynamic KNN fingerprint identification algorithm (VWD-KNN). Finally, experiments are carried out by using the dataset collected in both a closed laboratory and an open long corridor, and it is shown that the proposed algorithm substantially improves the localization accuracy comparing with other three classical algorithms.

Sign in / Sign up

Export Citation Format

Share Document