Indoor localization based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Network (WSN)
Localization is widely used in Wireless Sensor Networks (WSNs) to identify the current location of the sensor nodes. A WSN consist of thousands of nodes that make the installation of GPS on each sensor node expensive and moreover GPS may not provide exact localization results in an indoor environmen...
Saved in:
Main Author: | |
---|---|
Format: | Undergraduates Project Papers |
Language: | English |
Published: |
2019
|
Subjects: | |
Online Access: | http://umpir.ump.edu.my/id/eprint/27060/1/Indoor%20localization%20based%20on%20RSSI%20in%20WSN.pdf http://umpir.ump.edu.my/id/eprint/27060/ http://fypro.ump.edu.my/ethesis/index.php |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.ump.umpir.27060 |
---|---|
record_format |
eprints |
spelling |
my.ump.umpir.270602019-12-19T08:04:41Z http://umpir.ump.edu.my/id/eprint/27060/ Indoor localization based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Network (WSN) Nur Aina Auni, Ramlan QA75 Electronic computers. Computer science Localization is widely used in Wireless Sensor Networks (WSNs) to identify the current location of the sensor nodes. A WSN consist of thousands of nodes that make the installation of GPS on each sensor node expensive and moreover GPS may not provide exact localization results in an indoor environment. Localization is one of the most important challenges in WSNs, in view of the fact that it plays a significant part in many applications. Localization of node involves the activity of monitoring events, group discussion between the nearby sensors, routing the necessary information to the destination by keeping network coverage in check. In this research paper, Received Signal Strength Indicator (RSSI) based trilateration algorithm is proposed for localizing a sink node present in the network with minimal localization error. The position coordinates of the sink node is estimated based on the distance estimates and corresponding position coordinates of the anchor nodes present in the network. This work was performed in Contiki-OS with the help of built-in simulator COOJA. 2019-01 Undergraduates Project Papers NonPeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/27060/1/Indoor%20localization%20based%20on%20RSSI%20in%20WSN.pdf Nur Aina Auni, Ramlan (2019) Indoor localization based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Network (WSN). Faculty of Computer System & Software Engineering, Universiti Malaysia Pahang. http://fypro.ump.edu.my/ethesis/index.php |
institution |
Universiti Malaysia Pahang |
building |
UMP Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Malaysia Pahang |
content_source |
UMP Institutional Repository |
url_provider |
http://umpir.ump.edu.my/ |
language |
English |
topic |
QA75 Electronic computers. Computer science |
spellingShingle |
QA75 Electronic computers. Computer science Nur Aina Auni, Ramlan Indoor localization based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Network (WSN) |
description |
Localization is widely used in Wireless Sensor Networks (WSNs) to identify the current location of the sensor nodes. A WSN consist of thousands of nodes that make the installation of GPS on each sensor node expensive and moreover GPS may not provide exact localization results in an indoor environment. Localization is one of the most important challenges in WSNs, in view of the fact that it plays a significant part in many applications. Localization of node involves the activity of monitoring events, group discussion between the nearby sensors, routing the necessary information to the destination by keeping network coverage in check. In this research paper, Received Signal Strength Indicator (RSSI) based trilateration algorithm is proposed for localizing a sink node present in the network with minimal localization error. The position coordinates of the sink node is estimated based on the distance estimates and corresponding position coordinates of the anchor nodes present in the network. This work was performed in Contiki-OS with the help of built-in simulator COOJA. |
format |
Undergraduates Project Papers |
author |
Nur Aina Auni, Ramlan |
author_facet |
Nur Aina Auni, Ramlan |
author_sort |
Nur Aina Auni, Ramlan |
title |
Indoor localization based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Network (WSN) |
title_short |
Indoor localization based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Network (WSN) |
title_full |
Indoor localization based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Network (WSN) |
title_fullStr |
Indoor localization based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Network (WSN) |
title_full_unstemmed |
Indoor localization based on Received Signal Strength Indicator (RSSI) in Wireless Sensor Network (WSN) |
title_sort |
indoor localization based on received signal strength indicator (rssi) in wireless sensor network (wsn) |
publishDate |
2019 |
url |
http://umpir.ump.edu.my/id/eprint/27060/1/Indoor%20localization%20based%20on%20RSSI%20in%20WSN.pdf http://umpir.ump.edu.my/id/eprint/27060/ http://fypro.ump.edu.my/ethesis/index.php |
_version_ |
1654960276793982976 |
score |
13.211869 |