Wifi-based localisation datasets for No-GPS open areas using smart bins

M.A. Nassar; M. Hasan; Md. Khan; M. Sultana; Md. Hasan; L. Luxford; P. Cole; G. Oatley; P. Koutsakis

doi:10.1016/j.comnet.2020.107422

Back

Wifi-based localisation datasets for No-GPS open areas using smart bins

Journal article

Peer reviewed

Wifi-based localisation datasets for No-GPS open areas using smart bins

M.A. Nassar, M. Hasan, Md. Khan, M. Sultana, Md. Hasan, L. Luxford, P. Cole, G. Oatley and P. Koutsakis

Computer Networks, Vol.180, Art. 107422

2020

DOI: https://doi.org/10.1016/j.comnet.2020.107422

Files and links (1)

url

Link to Published Version *Subscription may be requiredView

Abstract

In recent years, Wifi-based localisation systems have gained significant interest because of the lack of Global Positioning System (GPS) signal in indoor and certain open areas. Over the past decade, many datasets have been introduced to enable researchers to compare different localisation techniques. Existing datasets, however, have failed to cover open areas such as parks in cases where GPS is still unavailable, and there is a lack of Wifi access points. Also, the existing datasets only focus on getting Wifi fingerprint collected and labelled by users. To the best of our knowledge, no dataset provides Received Signal Strengths (RSS) collected by Wireless Access Points (APs). In this work, we offer two datasets publicly. The first is the Fingerprint dataset in which four users generated 16,032 accurate and consistently labelled WiFi fingerprints for all available Reference Points (RPs) in a central and busy area of Murdoch University, known as Bush Court. The second is the APs dataset that includes 2,450,865 auto-generated records received from 1000 users’ devices, including the four users, associated with Wifi signal strengths. To overcome the Wifi coverage problem for the Bush Court, we attached our previously designed Wireless Sensor Nodes (WSNs) to existing garbage bins, enabling them to provide real-time environmental sensing and act as soft APs that sense MAC addresses and Wifi signals from surrounding devices.

Details

Title: Wifi-based localisation datasets for No-GPS open areas using smart bins
Authors/Creators: M.A. Nassar (Author/Creator) - Murdoch University
M. Hasan (Author/Creator) - Murdoch University
Md. Khan (Author/Creator)
M. Sultana (Author/Creator) - Murdoch University
Md. Hasan (Author/Creator)
L. Luxford (Author/Creator) - Global Smart Cities T/A yStop, Australia
P. Cole (Author/Creator) - Murdoch University
G. Oatley (Author/Creator) - Federation University
P. Koutsakis (Author/Creator) - Murdoch University
Publication Details: Computer Networks, Vol.180, Art. 107422
Publisher: Elsevier
Identifiers: 991005545261307891
Copyright: © 2020 Elsevier B.V.
Murdoch Affiliation: Information Technology, Mathematics and Statistics
Language: English
Resource Type: Journal article

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

Source: InCites

Metrics

105 Record Views

7 Times Cited - Web of Science

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types: Domestic collaboration
Citation topics: 4 Electrical Engineering, Electronics & Computer Science; 4.13 Telecommunications; 4.13.696 Wireless Localization
Web Of Science research areas: Computer Science, Hardware & Architecture; Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications
ESI research areas: Computer Science