scholarly journals Localisation of Inspection Probes in A Storage Tank

2021 ◽  
Vol 1 (2) ◽  
pp. 101-112
Author(s):  
Nurmi Elisya Rosli ◽  
Ali Sophian ◽  
Arselan Ashraf
Keyword(s):  
Storage Tank ◽  
Ieee 802.15.4 ◽  
Indoor Localization ◽  
Signal Strength ◽  
Positioning System ◽  
Wireless Technology ◽  
Received Signal Strength Indicator ◽  
Application System ◽  
Wireless Communication Protocols ◽  
Indoor Positioning System

Indoor Positioning System (IPS) has been widely used in today’s industry for the various purposes of locating people or objects such as inspection, navigation, and security. Many research works have been done to develop the system by using wireless technology such as Bluetooth and Wi-Fi. The techniques that can give some better performances in terms of accuracy have been investigated and developed. In this paper, ZigBee IEEE 802.15.4 wireless communication protocols are used to implement an indoor localization application system. The research is focusing more on analyzing the behaviour of Received Signal Strength Indicator (RSSI) reading under several conditions and locations by applying the Trilateration algorithm for localizing. The conditions are increasing the number of transmitters, experimented in the non-wireless connection room and wireless connection room by comparing the variation of RSSI values. Analysis of the result shows that the accuracy of the system was improved as the number of transmitters was increased.

scholarly journals PEOPLE’S PPRESENCE EFFECT ON WLAN-BASED IPS’ ACCURACY

2015 ◽  
Vol 77 (9) ◽  
Author(s):  
Iyad H Alshami ◽  
Noor Azurati Ahmad ◽  
Shamsul Sahibuddin
Keyword(s):  
Low Cost ◽  
Signal Strength ◽  
Access Point ◽  
Received Signal Strength ◽  
Positioning System ◽  
Indoor Environments ◽  
Received Signal Strength Indicator ◽  
Indoor Positioning System ◽  
Closed Environment ◽  
Presence Of People

In order to enable Location Based Service (LBS) closed environment, many technologies have been investigated to replace the Global Positioning System (GPS) in the localization process in indoor environments. WLAN is considered as the most suitable and powerful technology for Indoor Positioning System (IPS) due to its widespread coverage and low cost. Although WLAN Received Signal Strength Indicator (RSS) fingerprinting can be considered as the most accurate IPS method, this accuracy can be weakened due to WLAN RSS fluctuation. WLAN RSS fluctuates due to the multipath being influenced by obstacles presence. People presence under WLAN coverage can be considered as one of the main obstacles which can affect the WLAN-IPS accuracy. This research presents experimental results demonstrating that people’s presence between access point (AP) and mobile device (MD) reduces the received signal strength by -2dBm to -5dBm. This reduction in RSS can lead to distance error greater than or equal to 2m. Hence, any accurate IPS must consider the presence of people in the indoor environment. 

scholarly journals Accurate indoor positioning system based on modify nearest point technique

2022 ◽  
Vol 12 (2) ◽  
pp. 1593
Author(s):  
Omar Ibrahim Mustafa ◽  
Hawraa Lateef Joey ◽  
Noor Abd AlSalam ◽  
Ibrahim Zeghaiton Chaloob
Keyword(s):  
Indoor Localization ◽  
Signal Strength ◽  
Real Data ◽  
Reference Points ◽  
Positioning System ◽  
Indoor Environments ◽  
Nearest Point ◽  
The Impact ◽  
Indoor Positioning System

Wireless fidelity (Wi-Fi) is common technology for indoor environments that use to estimate required distances, to be used for indoor localization. Due to multiple source of noise and interference with other signal, the receive signal strength (RSS) measurements unstable. The impression about targets environments should be available to estimate accurate targets location. The Wi-Fi fingerprint technique is widely implemented to build database matching with real data, but the challenges are the way of collect accurate data to be the reference and the impact of different environments on signals measurements. In this paper, optimum system proposed based on modify nearest point (MNP). To implement the proposal, 78 points measured to be the reference points recorded in each environment around the targets. Also, the case study building is separated to 7 areas, where the segmentation of environments leads to ability of dynamic parameters assignments. Moreover, database based on optimum data collected at each time using 63 samples in each point and the average will be final measurements. Then, the nearest point into specific environment has been determined by compared with at least four points. The results show that the errors of indoor localization were less than (0.102 m).

scholarly journals DL-IPS: Deep Learning Based Indoor Positioning System for Improved Accuracy

2019 ◽  
Vol 8 (4) ◽  
pp. 10797-10801
Keyword(s):  
Deep Learning ◽  
Low Cost ◽  
Signal Strength ◽  
Low Energy ◽  
Positioning System ◽  
Received Signal Strength Indicator ◽  
Indoor Tracking ◽  
And Control ◽  
Improved Accuracy ◽  
Indoor Positioning System

Indoor tracking has evolved with various methods and well known these days. There are diverse types of solutions that concentrate on exactness, low cost, and control utilization within the field. Particularly in recent years, Received Signal Strength Indicator based positioning estimation have been getting popular. Still, the accuracy are not adequate, and there's no correct way chosen to overcome this issue. In this paper, we propose a strategy that leverage Deep Learning and Wi-Fi/BLE (Bluetooth Low Energy) Fingerprinting strategy to produce superior precise accuracy.

scholarly journals Indoor Positioning System (IPS) Berdasarkan Kekuatan Received Signal Strength Indicator (RSSI)

2018 ◽  
Vol 2 (01) ◽  
pp. 27-33
Author(s):  
Budi Rahmadya Rahmadya
Keyword(s):  
Signal Strength ◽  
Indoor Positioning ◽  
Received Signal Strength ◽  
Shopping Mall ◽  
Positioning System ◽  
Received Signal Strength Indicator ◽  
Indoor Positioning System

Shopping Mall merupakan area pusat perbelanjaan yang besar dan memiliki sistem keamanan seperti sistem layanan informasi yang dapat dimanfaatkan oleh konsumen untuk mendapatkan informasi yang dibutuhkan. Penggunaan sistem layanan informasi pada area Shopping Mall bagi konsumen terkadang sangat tidak efektif. Hal ini dikarenakan konsumen membutuhkan waktu yang lama dalam mendapatkan informasi, dimana konsumen terlebih dahulu harus mencari lokasi tempat sistem layanan informasi tersebut. Hal ini menjadikan sistem keamanan pada Shopping Mall menjadi lemah. Indoor Positioning System (IPS) merupakan sistem yang dapat digunakan untuk mengetahui posisi pengguna melalui kekuatan sinyal Wi-Fi yang didapat dalam gedung. Pada penelitian ini, penulis membuat suatu aplikasi android yang dapat digunakan untuk mengetahui posisi konsumen pada area Shopping Mall tersebut.

scholarly journals A Practical Evaluation of ML Algorithms for a Tag-Based BLE Indoor Positioning System

2020 ◽  
Vol 16 (08) ◽  
pp. 39
Author(s):  
Ashraf Tahat ◽  
Mohammed N Smadi ◽  
Mohammad Syouf
Keyword(s):  
Real Life ◽  
Signal Strength ◽  
Indoor Positioning ◽  
Positioning System ◽  
Economic Approach ◽  
Received Signal Strength Indicator ◽  
Office Space ◽  
Practical Evaluation ◽  
Online Tracking ◽  
Indoor Positioning System

In this paper, we evaluate the performance of machine learning (ML) algorithms employed in a commercial Bluetooth Low Energy (BLE) Indoor Positioning (IP) solution relying on practical measurements in a commercial office space setting.  The BLE IP system utilizing tags presents an ideal economic approach for large facilities with a limited number of tracking elements (gateways).  In this investigation, data collection campaigns were conducted in an indoor facility fitted with BLE gateways to aggregate Received Signal Strength Indicator (RSSI) <em>fingerprints</em>.  Performance of a collection of well-known ML algorithms in terms of accuracy of positioning of the desired objects, in addition to training complexity and online tracking speed were evaluated.  ML algorithms of increased accuracy and efficiency were identified and tabulated in both of the <em>offline</em> and <em>online</em> phases.  It is also envisaged that as part of this practical study, the results will serve to identify proper economical topologies and configuration in real-life installations for tag-based BLE IP systems.

scholarly journals An effective algorithm to overcome the practical hindrance for Wi-Fi based indoor positioning system

2020 ◽  
Vol 10 (1) ◽  
pp. 117-123
Author(s):  
Bhulakshmi Bonthu ◽  
M Subaji
Keyword(s):  
Signal Strength ◽  
Access Point ◽  
Indoor Positioning ◽  
Positioning System ◽  
Radio Waves ◽  
Direct Path ◽  
Received Signal Strength Indicator ◽  
Access Points ◽  
Measuring Techniques ◽  
Indoor Positioning System

AbstractIndoor tracking has evolved with various methods. The most popular method is using signal strength measuring techniques like triangulation, trilateration and fingerprinting, etc. Generally, these methods use the internal sensors of the smartphone. All these techniques require an adequate number of access point signals. The estimated positioning accuracy depends on the number of signals received at any point and precision of its signal (Wi-Fi radio waves) strength. In a practical environment, the received signal strength indicator (RSSI) of the access point is hindered by obstacles or blocks in the direct path or Line of sight. Such access points become an anomaly in the calculation of position. By detecting the anomaly access points and neglecting it during the computation of an indoor position will improve the accuracy of the positioning system. The proposed method, Practical Hindrance Avoidance in an Indoor Positioning System (PHA-IPS), eliminate the anomaly nodes while estimating the position, so then enhances the accuracy.

scholarly journals Design Space Exploration of a Multi-Model AI-Based Indoor Localization System

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 570
Author(s):  
Konstantinos Kotrotsios ◽  
Anastasios Fanariotis ◽  
Helen-Catherine Leligou ◽  
Theofanis Orphanoudakis
Keyword(s):  
Embedded System ◽  
Design Space Exploration ◽  
Design Space ◽  
Indoor Localization ◽  
Positioning System ◽  
Received Signal Strength Indicator ◽  
Interior Spaces ◽  
Reduction Methods ◽  
The Embedded System ◽  
Indoor Positioning System

In this paper, we present the results of a performance evaluation and optimization process of an indoor positioning system (IPS) designed to operate on portable as well as miniaturized embedded systems. The proposed method uses the Received Signal Strength Indicator (RSSI) values from multiple Bluetooth Low-Energy (BLE) beacons scattered around interior spaces. The beacon signals were received from the user devices and processed through an RSSI filter and a group of machine learning (ML) models, in an arrangement of one model per detected node. Finally, a multilateration problem was solved using as an input the inferred distances from the advertising nodes and returning the final position approximation. In this work, we first presented the evaluation of different ML models for inferring the distance between the devices and the installed beacons by applying different optimization algorithms. Then, we presented model reduction methods to implement the optimized algorithm on the embedded system by appropriately adapting it to its constraint resources and compared the results, demonstrating the efficiency of the proposed method.

scholarly journals Trilateration Method For Estimating Location in RSSI-Based Indoor Positioning System Using Zigbee Protocol

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Herryawan Pujiharsono ◽  
Duwi Utami ◽  
Rafina Destiarti Ainul
Keyword(s):  
Path Loss ◽  
Signal Strength ◽  
Indoor Positioning ◽  
Positioning System ◽  
Observation Area ◽  
Current Location ◽  
Zigbee Protocol ◽  
The Mean ◽  
Unknown Node ◽  
Indoor Positioning System

Wireless network technology that is used today is developing rapidly because of the increasing need for location information of an object with high accuracy. Global Positioning System (GPS) is a technology to estimate the current location. Unfortunately, GPS has a disadvantage of low accuracy of 10 meters when used indoors. Therefore, it began to be developed with the concept of an indoor positioning system. This is a technology used to estimate the location of objects in a building by utilizing WSN (Wireless Sensor Network). The purpose of this study is to estimate the location of the unknown nodes in the lecturer room as an object and obtain the accuracy of the system being tested. The positioning process is based on the received signal strength (RSSI) on the unknown node using the ZigBee module. The trilateration method is used to estimate unknown node located at the observation area based on the signal strength received at the time of testing. The result shows that the path loss coefficient value at the observation area is 0.9836 and the Mean Square Error of the test is 1.251 meters, which indicates that the system can be a solution to the indoor GPS problem.

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