scholarly journals Estimation of the number of people in an indoor environment based onWiFi received signal strength indicator

2021 ◽  
Vol 10 (3) ◽  
pp. 1475-1483
Author(s):  
Hakam Marwan Zaidan ◽  
Emad Ahmed Mohammed ◽  
Dheyaa Hussein Alhelal
Keyword(s):  
Indoor Environment ◽  
Polynomial Regression ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Line Of Sight ◽  
Concrete Wall ◽  
Received Signal Strength Indicator ◽  
The People ◽  
Two Stages ◽  
Non Line Of Sight

WiFi access points are widely spread everywhere in all our daily life routines. Using these devices to provide services other than the Internet is becoming familiar nowadays.This paper conducts an experimental study to estimate the number of people in an indoor environment through two system setups, line of sight, and non-line of sight. Relationship modeling between WiFi received signal and the number of people uses polynomial regression. The experiment comprised of two stages: first is the data collection from a controlled number of people. Then, the collected data used to train the system through polynomial regression. The second is testing the system’s effectiveness by applying it to an uncontrolled environment. Testing results revealed efficiency in using WiFi received signal strength to do the people counting (up to 60) because of the accuracy achievements of 93.17% in the line of sight system. The non-line of sight system disclosed randomness in the received signal strength indicator regardless of the change in the number of people. The  randomness is mainly caused by the fading effect of the concrete wall. Therefore it is inefficient to use the non-line of sight system in concrete buildings.

Modelling the Effect of Human Body around User on Signal Strength and Accuracy of Indoor Positioning

2020 ◽  
Vol 12 (7) ◽  
Author(s):  
Firdaus Firdaus ◽  
◽  
Noor Azurati Ahmad ◽  
Shamsul Sahibuddin ◽  
Rudzidatul Akmam Dziyauddin ◽  
...  
Keyword(s):  
Human Body ◽  
Signal Strength ◽  
Indoor Positioning ◽  
Position Estimation ◽  
Line Of Sight ◽  
Minimal Cost ◽  
The People ◽  
Indoor Positioning System ◽  
Presence Of People ◽  
Non Line Of Sight

WLAN indoor positioning system (IPS) has high accurate of position estimation and minimal cost. However, environmental conditions such as the people presence effect (PPE) greatly influence WLAN signal and it will decrease the accuracy. This research modelled the effect of people around user on signal strength and the accuracy. We have modelled the human body around user effects by proposed a general equation of decrease in signal strength as function of position, distance, and number of people. Signal strength decreased from 5 dBm to 1 dBm when people in line of sight (LOS) position, and start from 0.5 dBm to 0.3 dBm when people in non-line of sight (NLOS) position. The system accuracy decreases due to the presence of people. When the system is in NLOS case, the presence of people causes a decrease in accuracy from 33% to 57%. Then the accuracy decrease from 273% to 334% in LOS case.

The Improved Personnel Location Algorithm Based on RSSI

2013 ◽  
Vol 712-715 ◽  
pp. 2003-2006
Author(s):  
Sheng Mei Zhou ◽  
Ting Lei Huang
Keyword(s):  
Signal Strength ◽  
Wireless Sensor ◽  
Line Of Sight ◽  
Localization Algorithm ◽  
Matlab Simulation ◽  
Node Localization ◽  
Received Signal Strength Indicator ◽  
Positioning Accuracy ◽  
Location Algorithm ◽  
Non Line Of Sight

In the process of that based on the RSSI received signal strength indicator technique, resulting in the positioning accuracy is so low, since the simple RSSI, multipath, diffraction and non line of sight and other factors. In order to achieve higher accuracy node localization in wireless sensor, the paper is proposed based on the probability of recycling triangle centroid location algorithm in the RSSI technique,The probability of the cycle to handle triangle centroid localization algorithm. Through the Matlab simulation, compared with the traditional triangle centroid localization algorithm, the error is significantly reduced and positioning accuracy improved when the anchor point number exceeds a certain number.

Non-Line-of-Sight Identification and Mitigation Using Received Signal Strength

2015 ◽  
Vol 14 (3) ◽  
pp. 1689-1702 ◽  
Author(s):  
Zhuoling Xiao ◽  
Hongkai Wen ◽  
Andrew Markham ◽  
Niki Trigoni ◽  
Phil Blunsom ◽  
...  
Keyword(s):  
Signal Strength ◽  
Received Signal Strength ◽  
Line Of Sight ◽  
Non Line Of Sight

scholarly journals Design and Build Setup Mode Microcontroller-Based in Cars

2021 ◽  
Vol 11 (1) ◽  
pp. 50-54
Author(s):  
Alfan Tamamy ◽  
Koesmarijanto Koesmarijanto ◽  
Ridho Hendra Yoga Perdana
Keyword(s):  
Remote Control ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Line Of Sight ◽  
Infra Red ◽  
Motorized Vehicles ◽  
Bluetooth Communication ◽  
Thick Glass ◽  
Beam Range ◽  
Non Line Of Sight

People want a vehicle that is ready to use without having to wait for long or in the sense that the performance of an activity can run efficiently. With a remote control that can control the vehicle remotely, activities in setup mode will be more efficient. In general, remote control is used in motorized vehicles using Infra-red or Bluetooth communication with communication distance 60meters. So we need LoRa module that has longer beam range. The purpose of research is to design remote control and receiver that can control the vehicle such as opening vehicle door lock,  activating the AC, to the starter mode on the car contact with a wider range of sending and receiving information. The results of research indicate that LoRa module has received signal strength value (RSSI) of -65dBm when LOS (line of sight) at distance 10meters and RSSI of -66dBm at non-LOS (non-line of sight) at the same distance. SNR of 9.25dB when LOS and SNR of 6.0dB when non-LOS at distance 10meters. The research results of sending and receiving remote control data have a maximum distance when non-LOS with obstacles 5mm thick glass and 20 cars is 100 meters with a received signal strength of -112dBm. It can be concluded that for non-LOS connectivity between the LoRa SX1278 has an effectiveness distance at 50meters with an RSSI value of -99dBm and an SNR of 0.25dB, for a LOS condition it has an effectiveness at distance 50meters with RSSI value of -96dBm and SNR of 9dB.

scholarly journals Studi Performansi Jarak Jangkauan Lora-Dragino Sebagai Infrastruktur Konektifitas Nirkabel Pada WP-LAN

2019 ◽  
Vol 15 (1) ◽  
pp. 47 ◽  
Author(s):  
Eko Murdyantoro ◽  
Imron Rosyadi ◽  
Hilmi Septian
Keyword(s):  
Internet Of Things ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Line Of Sight ◽  
Received Signal Strength Indicator

Dalam sistem Internet of things (IoT), berbagai macam obyek fisik disekitar manusia akan disensor dan direpresentasikan menjadi data digital untuk mendukung produktifitas manusia. Sensor dan aktuator sebagai <em>node</em> akan terhubung satu sama lain untuk diproses oleh sistem cerdas. Ada beberapa pilihan teknologi bagi pengembang sistem IoT untuk mengimplementasikan konektivitas antar <em>node</em> tersebut. Teknologi konektivitas nirkabel tersebut antara lain dengan modul GSM, wifi, bluetooth LE, Zigbee, NB-IoT, Sigfox dan LoRa yang menjadi topik studi ini. Teknologi LoRa dikembangkan terutama diproyeksikan sebagai infrastruktur konektifitas nirkabel pada sistem IoT. Beberapa potensi kelebihan fitur LoRa yang diklaim LoRa Alliance antara lain berdaya rendah; dapat mendukung konektifitas IoT skala luas sampai ribuan <em>node</em> dalam satu sel; dan termasuk dalam kategori jangkauan radio jarak jauh. Studi ini bertujuan untuk menguji performansi jarak jangkauan radio dari modul LoRa OLG01 pada sistem IoT yang dikembangkan pada frekuensi ISM 915MHz di atmosfer Indonesia. Dalam studi ini konfigurasikan <em>node</em> yang terhubung ke <em>gateway</em> agar dapat terhubung ke internet menjadi sistem IoT dengan set SF=7 dan BW= 125 kHz. Pembahasan dibatasi pada pengujian performansi jarak jangkauan dengan parameter RSSI (Received Signal Strength Indicator) dan jarak saat LOS (<em>line of sight</em>) dan non LOS (ada halangan). Jangkauan LoRa saat ini yang berhasil diukur sekitar radius 400m. Jarak jangkauan ini masih belum sesuai dengan spesifikasi yang diharapkan yaitu sampai radius 5 km, sehingga masih perlu dicari solusi dan konfigurasi yang lebih optimal

RADIO PROPAGATION CHARACTERISTICS OF INDOOR LOCATION SYSTEM BASED ON RSSI AT 490 MHz

2014 ◽  
Vol 23 (07) ◽  
pp. 1450094 ◽  
Author(s):  
WEIHONG FAN ◽  
MAJID AHMADI ◽  
FENG XUE
Keyword(s):  
Indoor Environment ◽  
Path Loss ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Propagation Characteristic ◽  
Radio Propagation ◽  
Test Results ◽  
Received Signal Strength Indicator ◽  
Indoor Location ◽  
Localization And Tracking

Localization and tracking technology based on received signal strength indicator (RSSI) is one of the most popular topics because of its low demand on hardware and cost. But the complexity of the indoor environment, leads to the uncertainty of the radio propagation which can seriously affect the positioning accuracy based on the received signal strength. Focused on the wall reflection in the indoor environment, the radio propagation characteristic based on ray-tracing model is analyzed and one strategy for the near wall localization is presented. The actual hardware platform and experimental test results show the applicability of the empirical logarithmic path loss model for localization and the effect of the wall reflection.

scholarly journals Indoor localization system based on virtual access points with filtering schemes

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986613 ◽  
Author(s):  
Dong Myung Lee ◽  
Boney Labinghisa
Keyword(s):  
Kalman Filter ◽  
Indoor Environment ◽  
Performance Testing ◽  
Signal Strength ◽  
Access Point ◽  
Received Signal Strength ◽  
Indoor Environments ◽  
Received Signal Strength Indicator ◽  
Access Points ◽  
Error Distance

In indoor positioning techniques, Wi-Fi is one of the most used technology because of its availability and cost-effectiveness. Access points are usually the main source of Wi-Fi signals in an indoor environment. If access points are optimized to cover the indoor area, this could improve Wi-Fi signal distribution. This article proposed an alternative to optimizing access point placement and distribution by introducing virtual access points that can be virtually placed in any part of the indoor environment without installation of actual access points. Virtual access points will be created heuristically by correlating received signal strength indicator of already existing access points and through linear regression. After introducing virtual access points in the indoor environment, next will be the addition of filters to improve signal fluctuation and reduce noise interference. Kalman filter has been previously used together with virtual access point and showed improvement by decreasing error distance of Wi-Fi fingerprinting results. This article also aims to include particle filter in the system to further improve localization and test its effectiveness when paired with Kalman filter. The performance testing of the algorithm in different indoor environments resulted in 3.18 and 3.59 m error distances. An improvement was added on the system by using relative distances instead of received signal strength indicator values in distance estimation and gave an error distance average of 1.85 m.

scholarly journals Analisis Performa Bluetooth pada Sistem Alarm Pengingat Barang yang Tertinggal dengan Smartphone Android

2021 ◽  
Vol 17 (3) ◽  
Author(s):  
Rafiqmia Khairuddin Nur Hammam ◽  
Hidayat Nur Isnianto ◽  
Sri Lestari ◽  
Y. Wahyo Setiyono
Keyword(s):  
Packet Loss ◽  
Signal Strength ◽  
Smartphone Application ◽  
Received Signal Strength ◽  
Line Of Sight ◽  
Test Results ◽  
Received Signal Strength Indicator ◽  
Measured Distance ◽  
Receiver Module ◽  
Point To Point

Someone sometimes forgets to put their belongings so that they leave them somewhere, it will pose a risk of losing their belongings. To solve this problem, a reminder is needed so that it is expected to minimize the risk of loss. This device implements point-to-point communication from the Bluetooth Low Energy AT-09 transmitter module with Arduino Nano and the receiver module with an Android smartphone. This reminder device will activate an alarm on the Android smartphone application when the two modules are more than 5 meters away. The measured distance is converted from the Received Signal Strength Indicator (RSSI) value received by the smartphone which is affected by obstructions, packet loss, and delay. Based on the test results, at a distance of 5 meters, the system can be connected and work properly, in unobstructed conditions (Line of Sight) or obstructed conditions (Non-Line of Sight). In the blocked condition, it has a packet loss of 1.1% to 4.4%, the received signal strength (RSSI) has decreased the value to a difference of -8 dBm, and the delay time is 2 seconds.

scholarly journals Inertial measurement unit–aided dual-frequency radio frequency identification localization in line-of-sight and non-line-of-sight hybrid environment

2018 ◽  
Vol 14 (3) ◽  
pp. 155014771876203
Author(s):  
Jie Wu ◽  
Minghua Zhu ◽  
Bo Xiao ◽  
Wei He
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
Inertial Measurement Unit ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Measurement Unit ◽  
Line Of Sight ◽  
Inertial Measurement ◽  
Frequency Identification ◽  
Non Line Of Sight

The mitigation of non-line-of-sight propagation conditions is one of main challenges in wireless signal–based indoor localization. When radio frequency identification localization technology is applied in applications, the received signal strength fluctuates frequently due to the shade and multipath effect of radio frequency signal, which could result in localization inaccuracy. In particular, when tag carriers are walking in line-of-sight and non-line-of-sight hybrid environment, great attenuation of received signal strength will happen, which would result in great positioning deviation. The article puts forward a dual-frequency radio frequency identification–based indoor localization approach in line-of-sight–non-line-of-sight hybrid environment with the help of inertial measurement unit. Dual-frequency radio frequency identification includes passive radio frequency identification and active radio frequency identification. Passive radio frequency identification is used to assist in determining the tag initial location with passive reader. Active radio frequency identification is used to locate the tag and send the sensor information to active radio frequency identification readers. The proposed method includes three improvements over previous received signal strength–based positioning methods: inertial measurement unit–aided received signal strength filtering, inertial measurement unit–aided line-of-sight/non-line-of-sight distinguishing, and inertial measurement unit–aided line-of-sight/non-line-of-sight environment switching. Also, Cramér–Rao low bound is calculated to prove theoretically that indoor positioning accuracy for the proposed method in line-of-sight and non-line-of-sight mixed environment is higher than position precision using only received signal strength information. Experiments are conducted to show that the proposed method can reduce the mean positioning error to around 3 m without site survey.

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