Big data management in participatory sensing: Issues, trends and future directions
Participatory sensing has become an emerging technology of this era owing to its low cost in big sensor data collection. Prior to participatory sensing, large-scale deployment complexities were found in wireless sensor networks when collecting data from widespread resources. Participatory sensing sy...
Saved in:
Main Authors: | , , , , , , , , |
---|---|
Format: | Article |
Published: |
Elsevier
2020
|
Subjects: | |
Online Access: | http://eprints.um.edu.my/36653/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.um.eprints.36653 |
---|---|
record_format |
eprints |
spelling |
my.um.eprints.366532024-08-14T08:24:13Z http://eprints.um.edu.my/36653/ Big data management in participatory sensing: Issues, trends and future directions Karim, Ahmad Siddiqa, Aisha Safdar, Zanab Razzaq, Maham Gillani, Syeda Anum Tahir, Huma Kiran, Sana Ahmed, Ejaz Imran, Muhammad QA75 Electronic computers. Computer science Participatory sensing has become an emerging technology of this era owing to its low cost in big sensor data collection. Prior to participatory sensing, large-scale deployment complexities were found in wireless sensor networks when collecting data from widespread resources. Participatory sensing systems employ handheld devices as sensors to collect data from communities and transmit to the cloud, where data are further analyzed by expert systems. The processes involved in participatory sensing, such as data collection, transmission, analysis, and visualization, exhibit certain management issues. This study aims to identify big data management issues that must be addressed at the cloud side during data processing and storing and at the participant side during data collection and visualization. It then proposes a framework for big data management in participatory sensing to resolve the contemporary big data management issues on the basis of suggested principles. Moreover, this work presents case studies to elaborate the existence of the highlighted issues. Finally, the limitations, recommendations, and future research directions for academia and industry in the domain of participatory sensing are discussed. (C) 2017 Published by Elsevier B.V. Elsevier 2020-06 Article PeerReviewed Karim, Ahmad and Siddiqa, Aisha and Safdar, Zanab and Razzaq, Maham and Gillani, Syeda Anum and Tahir, Huma and Kiran, Sana and Ahmed, Ejaz and Imran, Muhammad (2020) Big data management in participatory sensing: Issues, trends and future directions. Future generation computer systems-the international journal of Escience, 107. pp. 942-955. ISSN 0167739X, |
institution |
Universiti Malaya |
building |
UM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Malaya |
content_source |
UM Research Repository |
url_provider |
http://eprints.um.edu.my/ |
topic |
QA75 Electronic computers. Computer science |
spellingShingle |
QA75 Electronic computers. Computer science Karim, Ahmad Siddiqa, Aisha Safdar, Zanab Razzaq, Maham Gillani, Syeda Anum Tahir, Huma Kiran, Sana Ahmed, Ejaz Imran, Muhammad Big data management in participatory sensing: Issues, trends and future directions |
description |
Participatory sensing has become an emerging technology of this era owing to its low cost in big sensor data collection. Prior to participatory sensing, large-scale deployment complexities were found in wireless sensor networks when collecting data from widespread resources. Participatory sensing systems employ handheld devices as sensors to collect data from communities and transmit to the cloud, where data are further analyzed by expert systems. The processes involved in participatory sensing, such as data collection, transmission, analysis, and visualization, exhibit certain management issues. This study aims to identify big data management issues that must be addressed at the cloud side during data processing and storing and at the participant side during data collection and visualization. It then proposes a framework for big data management in participatory sensing to resolve the contemporary big data management issues on the basis of suggested principles. Moreover, this work presents case studies to elaborate the existence of the highlighted issues. Finally, the limitations, recommendations, and future research directions for academia and industry in the domain of participatory sensing are discussed. (C) 2017 Published by Elsevier B.V. |
format |
Article |
author |
Karim, Ahmad Siddiqa, Aisha Safdar, Zanab Razzaq, Maham Gillani, Syeda Anum Tahir, Huma Kiran, Sana Ahmed, Ejaz Imran, Muhammad |
author_facet |
Karim, Ahmad Siddiqa, Aisha Safdar, Zanab Razzaq, Maham Gillani, Syeda Anum Tahir, Huma Kiran, Sana Ahmed, Ejaz Imran, Muhammad |
author_sort |
Karim, Ahmad |
title |
Big data management in participatory sensing: Issues, trends and future directions |
title_short |
Big data management in participatory sensing: Issues, trends and future directions |
title_full |
Big data management in participatory sensing: Issues, trends and future directions |
title_fullStr |
Big data management in participatory sensing: Issues, trends and future directions |
title_full_unstemmed |
Big data management in participatory sensing: Issues, trends and future directions |
title_sort |
big data management in participatory sensing: issues, trends and future directions |
publisher |
Elsevier |
publishDate |
2020 |
url |
http://eprints.um.edu.my/36653/ |
_version_ |
1809136910661058560 |
score |
13.19449 |