scholarly journals Feasibility of LoRa for Smart Home Indoor Localization

2021 ◽  
Vol 11 (1) ◽  
pp. 415
Author(s):  
Kyungki Kim ◽  
Sining Li ◽  
Milad Heydariaan ◽  
Nour Smaoui ◽  
Omprakash Gnawali ◽  
...  
Keyword(s):  
Low Power ◽  
Long Range ◽  
Radio Frequency Identification ◽  
Indoor Localization ◽  
Low Cost ◽  
Smart Homes ◽  
Ultra Wideband ◽  
Line Of Sight ◽  
Wireless Technologies ◽  
Better Than

With the advancement of low-power and low-cost wireless technologies in the past few years, the Internet of Things (IoT) has been growing rapidly in numerous areas of Industry 4.0 and smart homes. With the development of many applications for the IoT, indoor localization, i.e., the capability to determine the physical location of people or devices, has become an important component of smart homes. Various wireless technologies have been used for indoor localization including WiFi, ultra-wideband (UWB), Bluetooth low energy (BLE), radio-frequency identification (RFID), and LoRa. The ability of low-cost long range (LoRa) radios for low-power and long-range communication has made this radio technology a suitable candidate for many indoor and outdoor IoT applications. Additionally, research studies have shown the feasibility of localization with LoRa radios. However, indoor localization with LoRa is not adequately explored at the home level, where the localization area is relatively smaller than offices and corporate buildings. In this study, we first explore the feasibility of ranging with LoRa. Then, we conduct experiments to demonstrate the capability of LoRa for accurate and precise indoor localization in a typical apartment setting. Our experimental results show that LoRa-based indoor localization has an accuracy better than 1.6 m in line-of-sight scenario and 3.2 m in extreme non-line-of-sight scenario with a precision better than 25 cm in all cases, without using any data filtering on the location estimates.

scholarly journals Ultra-Low-Power, High-Accuracy 434 MHz Indoor Positioning System for Smart Homes Leveraging Machine Learning Models

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1401
Author(s):  
Haq Nawaz ◽  
Ahsen Tahir ◽  
Nauman Ahmed ◽  
Ubaid U. Fayyaz ◽  
Tayyeb Mahmood ◽  
...  
Keyword(s):  
Low Power ◽  
Indoor Localization ◽  
Low Cost ◽  
Smart Homes ◽  
Indoor Positioning ◽  
High Accuracy ◽  
Positioning System ◽  
Telemetry Data ◽  
Ultra Low Power ◽  
Indoor Positioning System

Global navigation satellite systems have been used for reliable location-based services in outdoor environments. However, satellite-based systems are not suitable for indoor positioning due to low signal power inside buildings and low accuracy of 5 m. Future smart homes demand low-cost, high-accuracy and low-power indoor positioning systems that can provide accuracy of less than 5 m and enable battery operation for mobility and long-term use. We propose and implement an intelligent, highly accurate and low-power indoor positioning system for smart homes leveraging Gaussian Process Regression (GPR) model using information-theoretic gain based on reduction in differential entropy. The system is based on Time Difference of Arrival (TDOA) and uses ultra-low-power radio transceivers working at 434 MHz. The system has been deployed and tested using indoor measurements for two-dimensional (2D) positioning. In addition, the proposed system provides dual functionality with the same wireless links used for receiving telemetry data, with configurable data rates of up to 600 Kbauds. The implemented system integrates the time difference pulses obtained from the differential circuitry to determine the radio frequency (RF) transmitter node positions. The implemented system provides a high positioning accuracy of 0.68 m and 1.08 m for outdoor and indoor localization, respectively, when using GPR machine learning models, and provides telemetry data reception of 250 Kbauds. The system enables low-power battery operation with consumption of <200 mW power with ultra-low-power CC1101 radio transceivers and additional circuits with a differential amplifier. The proposed system provides low-cost, low-power and high-accuracy indoor localization and is an essential element of public well-being in future smart homes.

scholarly journals Indoor Positioning Method Based on Infrared Vision and UWB Fusion

2021 ◽  
Vol 2078 (1) ◽  
pp. 012070
Author(s):  
Qianrong Zhang ◽  
Yi Li
Keyword(s):  
Real Time ◽  
Indoor Localization ◽  
Low Cost ◽  
Ultra Wideband ◽  
Coverage Area ◽  
Positioning Accuracy ◽  
Mobile Vehicle ◽  
Positioning Method ◽  
Positioning Algorithm ◽  
Infrared Vision

Abstract Ultra-wideband (UWB) has broad application prospects in the field of indoor localization. In order to make up for the shortcomings of ultra-wideband that is easily affected by the environment, a positioning method based on the fusion of infrared vision and ultra-wideband is proposed. Infrared vision assists locating by identifying artificial landmarks attached to the ceiling. UWB uses an adaptive weight positioning algorithm to improve the positioning accuracy of the edge of the UWB positioning coverage area. Extended Kalman filter (EKF) is used to fuse the real-time location information of the two. Finally, the intelligent mobile vehicle-mounted platform is used to collect infrared images and UWB ranging information in the indoor environment to verify the fusion method. Experimental results show that the fusion positioning method is better than any positioning method, has the advantages of low cost, real-time performance, and robustness, and can achieve centimeter-level positioning accuracy.

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 Identification of NLOS and Multi-Path Conditions in UWB Localization Using Machine Learning Methods

2020 ◽  
Vol 10 (11) ◽  
pp. 3980 ◽  
Author(s):  
Cung Lian Sang ◽  
Bastian Steinhagen ◽  
Jonas Dominik Homburg ◽  
Michael Adams ◽  
Marc Hesse ◽  
...  
Keyword(s):  
Machine Learning ◽  
Indoor Localization ◽  
Measurement Data ◽  
Ultra Wideband ◽  
Machine Learning Techniques ◽  
Line Of Sight ◽  
Support Vector ◽  
Case Scenario ◽  
Worst Case ◽  
Worst Case Scenario

In ultra-wideband (UWB)-based wireless ranging or distance measurement, differentiation between line-of-sight (LOS), non-line-of-sight (NLOS), and multi-path (MP) conditions is important for precise indoor localization. This is because the accuracy of the reported measured distance in UWB ranging systems is directly affected by the measurement conditions (LOS, NLOS, or MP). However, the major contributions in the literature only address the binary classification between LOS and NLOS in UWB ranging systems. The MP condition is usually ignored. In fact, the MP condition also has a significant impact on the ranging errors of the UWB compared to the direct LOS measurement results. However, the magnitudes of the error contained in MP conditions are generally lower than completely blocked NLOS scenarios. This paper addresses machine learning techniques for identification of the three mentioned classes (LOS, NLOS, and MP) in the UWB indoor localization system using an experimental dataset. The dataset was collected in different conditions in different scenarios in indoor environments. Using the collected real measurement data, we compared three machine learning (ML) classifiers, i.e., support vector machine (SVM), random forest (RF) based on an ensemble learning method, and multilayer perceptron (MLP) based on a deep artificial neural network, in terms of their performance. The results showed that applying ML methods in UWB ranging systems was effective in the identification of the above-three mentioned classes. Specifically, the overall accuracy reached up to 91.9% in the best-case scenario and 72.9% in the worst-case scenario. Regarding the F1-score, it was 0.92 in the best-case and 0.69 in the worst-case scenario. For reproducible results and further exploration, we provide the publicly accessible experimental research data discussed in this paper at PUB (Publications at Bielefeld University). The evaluations of the three classifiers are conducted using the open-source Python machine learning library scikit-learn.

Bluetooth Hands Free System for Fixed Telephone Research

2012 ◽  
Vol 198-199 ◽  
pp. 1603-1608
Author(s):  
Qing Hua Shang ◽  
Ping Liu
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
Mobile Phones ◽  
Daily Life ◽  
Low Cost ◽  
Low Power Consumption ◽  
Wireless Technology ◽  
Free System ◽  
Wireless Technologies ◽  
The Stability

Wireless technology has walked into the People's Daily life, Bluetooth technology comes to the fore in so many wireless technologies with its low power consumption, low cost and other characteristics. Bluetooth technology is used widely, we can see it in mobile phones or in our cars, it seems that Bluetooth technology has penetrated into every aspect of our lives. Even so, the combination of Bluetooth technology and fixed telephone still has a very big development space. If the stability of the fixed telephone combined with the flexible of Bluetooth technology, it will give the life of people a lot of convenience. This paper will introduces the Bluetooth hands free system for fixed telephone, it is such a product that it will make Bluetooth technology and common fixed phone combined, and make it a reality that people can use common Bluetooth headset to answer or call a fixed telephone.

LoRaWAN for an IoT-based environmental monitoring application in Tirana city

2021 ◽  
Author(s):  
Evjola Spaho ◽  
Aleksandër Biberaj ◽  
Ares Tahiraga
Keyword(s):  
Low Power ◽  
Environmental Monitoring ◽  
Long Range ◽  
Low Cost ◽  
Wide Area ◽  
Wide Area Networks ◽  
Area Network ◽  
Wide Area Network ◽  
Long Distance ◽  
Monitoring Application

AbstractRecently, low power wide area networks are attracting a lot of attention by the research community. They are wireless technologies characterized by large coverage area, low bandwidth and long battery life. One of these low power wide area networks technologies, the long range wide area network, can be used for different monitoring applications for health, agriculture, traffic, smart city.In this paper, different simulations and experiments are conducted to implement a low-cost long-range wide area network environmental monitoring application for Tirana city in Albania. Simulation and experimental data are compared and similar results were obtained. In the low-cost implemented system, the gateway can communicate with the sensors placed in strategic positions with long distance covered also using Radio Mobile software.

scholarly journals NLOS Identification and Mitigation Using Low-Cost UWB Devices

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3464 ◽  
Author(s):  
Valentín Barral ◽  
Carlos J. Escudero ◽  
José A. García-Naya ◽  
Roberto Maneiro-Catoira
Keyword(s):  
Low Cost ◽  
Estimation Error ◽  
Ultra Wideband ◽  
Line Of Sight ◽  
Distance Measurements ◽  
Indoor Location ◽  
Indoor Scenarios ◽  
Indoor Location Systems ◽  
Clear Line ◽  
Non Line Of Sight

Indoor location systems based on ultra-wideband (UWB) technology have become very popular in recent years following the introduction of a number of low-cost devices on the market capable of providing accurate distance measurements. Although promising, UWB devices also suffer from the classic problems found when working in indoor scenarios, especially when there is no a clear line-of-sight (LOS) between the emitter and the receiver, causing the estimation error to increase up to several meters. In this work, machine learning (ML) techniques are employed to analyze several sets of real UWB measurements, captured in different scenarios, to try to identify the measurements facing non-line-of-sight (NLOS) propagation condition. Additionally, an ulterior process is carried out to mitigate the deviation of these measurements from the actual distance value between the devices. The results show that ML techniques are suitable to identify NLOS propagation conditions and also to mitigate the error of the estimates when there is LOS between the emitter and the receiver.

An Improved Frequency Agility Mechanism for SimpliciTI Protocol

2014 ◽  
Vol 543-547 ◽  
pp. 3486-3489 ◽  
Author(s):  
Jun Qiang Wang ◽  
Jing Wu
Keyword(s):  
Low Power ◽  
Low Cost ◽  
Sensor Nodes ◽  
Channel Migration ◽  
Development Cycle ◽  
Short Development Cycle ◽  
Specific Frequency ◽  
Simulation Results ◽  
The Impact ◽  
Better Than

The rapid growth of application for low-cost, low power sensor nodes based on WSN brings its own challenges. SimpliciTI is a simple low-power RF network protocol that with open Source, flexibility, and low-cost, short development cycle and so on. Aiming at the blindness problem of channel migration when this specific frequency is noisy, We presented PSCP-FA(periodic synchronism and channel prediction Frequency agility) which accomplish the channel agility predictable. Furthermore, we evaluated the impact of energy of efficiency compared with S-MAC and FA. Our simulation results show that PSCP-FA performs better than S-MAC and FA.

scholarly journals LoPT : LoRa Penetration Testing Tool

2019 ◽  
Vol 8 (9S2) ◽  
pp. 374-379
Keyword(s):  
Low Power ◽  
Long Range ◽  
Modern World ◽  
Wireless Technologies ◽  
Penetration Testing ◽  
Steady Rate ◽  
Testing Tool ◽  
Iot Devices ◽  
Long Range Communication ◽  
Security Enhancements

The advent of Wireless technologies and IOT are currently ruling the modern world. Everything is going to become Things in future. As the technology progresses , the security of those technologies must also progress with an steady rate. Security tools which will help us to analyze these advanced security enhancements and protocols implemented. In this study , we are going to implement new security tool which concentrates on penetration testing of one such IOT protocol. This tool concentrates on the protocol named LoRa used for wireless long range communication in IOT. The proposed tool will explore all the possible attacks on LoRa protocol which we will see about in detail in the upcoming sections. LoPT is a new penetration testing tool which will work on LoRa (Long Range),a wireless standard used for long range low power communication on IOT devices primarily. This newly bloomed flower performs an effective domination on the field of IOT. Currently there is no existing penetration testing tool for LoRa. Though LoRa has its inbuilt security , there are major vulnerabilities which can be explored . This tool is built primarily on the concept of There’s no such thing as 100

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