An Improved RSSI Location Algorithm Suitable for Digital Workshop

Test Results ◽

Positioning Accuracy ◽

Automatic Guided Vehicles ◽

Location Algorithm ◽

Application Requirements

Relying on the background of constructing digital workshop, an improved RSSI (Received Signal Strength Indicator) location algorithm is introduced in this paper. At first, the application requirements of RSSI location algorithm are discussed from cargo tracking, instrument management and automatic guided vehicles three aspects; and then focuses on the improvements of the new RSSI location algorithm. The test results and analysis show that the positioning accuracy up to 0.89 meter by applying the new algorithm, and it can meet positioning requirements of digital workshop.

The Improved Personnel Location Algorithm Based on RSSI

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.712-715.2003 ◽

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 ◽

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.

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013) ◽

A Refined Concentric Anchor-Beacons Location Algorithm for Wireless Sensor Networks Based on Received Signal Strength Indicator

10.2991/iccsee.2013.648 ◽

2013 ◽

Author(s):

Kun Zhang ◽

Can Zhang ◽

He Chen ◽

Xiaohu Yin

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Signal Strength ◽

Wireless Sensor ◽

Location Algorithm

A quadratic weighted centroid algorithm for tunnel personnel positioning

International Journal of Distributed Sensor Networks ◽

10.1177/1550147720917021 ◽

2020 ◽

Vol 16 (4) ◽

pp. 155014772091702

Author(s):

Haiying Wang ◽

Linhao Liang ◽

Jian Xu ◽

Hui She ◽

Wuxiang Li

Keyword(s):

Signal Strength ◽

Weighting Factor ◽

Gaussian Filter ◽

Positioning Accuracy ◽

Filter Model ◽

Positioning Systems ◽

Centroid Algorithm ◽

Positioning Algorithm

To improve the accuracy and generalization of tunnel personnel positioning systems, this article proposes a quadratic weighted centroid algorithm. By adopting a Gaussian filter model to improve the range accuracy of the received signal strength indicator algorithm and combining the centroid algorithm and weighting factor with a trilateration positioning model, a quadratic weighted centroid algorithm is proposed to improve the positioning accuracy of unknown positioning nodes. The key ideas behind the quadratic weighted centroid algorithm include an optimization of the received signal strength indicator range value scheme, a centroid algorithm based on trilateral measurement positioning, and a weighting factor to improve the positioning accuracy of the trilateral centroid positioning algorithm. Compared with the centroid algorithm, the Min-Max multilateration algorithm, and the weighted centroid based on distance algorithm, the simulation results showed that (1) the positioning performance of the quadratic weighted centroid algorithm was superior to the other three algorithms; (2) when the reference nodes were symmetrically arranged, the positioning accuracy was higher than a fold line layout; and (3) when the lateral reference node spacing was extended from 20 to 30 m, the average positioning error met positioning accuracy requirements, which could reduce overall system costs.

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

Journal of Circuits System and Computers ◽

10.1142/s0218126614500947 ◽

2014 ◽

Vol 23 (07) ◽

pp. 1450094 ◽

Cited By ~ 1

Author(s):

WEIHONG FAN ◽

MAJID AHMADI ◽

FENG XUE

Keyword(s):

Indoor Environment ◽

Path Loss ◽

Signal Strength ◽

Propagation Characteristic ◽

Radio Propagation ◽

Test Results ◽

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.

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

Jurnal Rekayasa Elektrika ◽

10.17529/jre.v17i3.20648 ◽

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 ◽

Line Of Sight ◽

Test Results ◽

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.

A Refined Concentric Anchor-Beacons Location Algorithm for Wireless Sensor Networks Based on Received Signal Strength Indicator

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.347-350.1860 ◽

2013 ◽

Vol 347-350 ◽

pp. 1860-1863

Author(s):

Kun Zhang ◽

Can Zhang ◽

Chen He ◽

Xiao Hu Yin

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Signal Strength ◽

Wireless Sensor ◽

Localization Algorithm ◽

Localization Accuracy ◽

Location Algorithm ◽

Algorithm Base

As the development of technology, the wireless sensor networks (WSN) have a wide spread usage. And people pay more attention on the localization algorithm, as the key technology of WSN, there have been many method of self-localization. The concentric anchor-beacons (CAB) location algorithm is one of the most practical one, which is a range-free WSN localization algorithm. In order to further improve the accuracy of localizing nodes, an improved CAB location algorithm base on Received Signal Strength Indicator (RSSI) is proposed. The RSSI is used to measure the distance between two anchors and compare with the practical distance. Then the environment between two anchors can be simulated. At last the communication radius of anchors can be optimized. And the common area of the anchors in the process of localizing nodes can be reduced. Then the accuracy is improved. By simulation, the localization accuracy is improved when the anchors numbers is more than a certain percentage.

KAJIAN KEKUATAN SINYAL RADIO (RSSI) XBEE DALAM RANGKA PEMASANGAN LANDSLIDE EARLY WARNING SYSTEM (LEWS) DI KABUPATEN GARUT, TASIKMALAYA DAN MAJALENGKA

Jurnal Alami : Jurnal Teknologi Reduksi Risiko Bencana ◽

10.29122/alami.v3i2.3731 ◽

2019 ◽

Vol 3 (2) ◽

pp. 88

Author(s):

Riski Fitriani

Keyword(s):

Early Warning ◽

Early Warning System ◽

Warning System ◽

Signal Strength ◽

Landslide Early Warning ◽

Point To Point

Salah satu inovasi untuk menanggulangi longsor adalah dengan melakukan pemasangan Landslide Early Warning System (LEWS). Media transmisi data dari LEWS yang dikembangkan menggunakan sinyal radio Xbee. Sehingga sebelum dilakukan pemasangan LEWS, perlu dilakukan kajian kekuatan sinyal tersebut di lokasi yang akan terpasang yaitu Garut, Tasikmalaya, dan Majalengka. Kajian dilakukan menggunakan 2 jenis Xbee yaitu Xbee Pro S2B 2,4 GHz dan Xbee Pro S5 868 MHz. Setelah dilakukan kajian, Xbee 2,4 GHz tidak dapat digunakan di lokasi pengujian Garut dan Majalengka karena jarak modul induk dan anak cukup jauh serta terlalu banyak obstacle. Topologi yang digunakan yaitu topologi pair/point to point, dengan mengukur nilai RSSI menggunakan software XCTU. Semakin kecil nilai Received Signal Strength Indicator (RSSI) dari nilai receive sensitivity Xbee maka kualitas sinyal semakin baik. Pengukuran dilakukan dengan meninggikan antena Xbee dengan beberapa variasi ketinggian untuk mendapatkan kualitas sinyal yang lebih baik. Hasilnya diperoleh beberapa rekomendasi tinggi minimal antena Xbee yang terpasang di tiap lokasi modul anak pada 3 kabupaten.