Disaster resilient mesh network using LoRa and Nervenet
When a natural disaster event happens, it could cause regional cellular network outages and hence disable network communication within the affected area. If a resilient network is implemented, alert messages with sufficient information can be sent over the Internet to provide a nationwide response....
Saved in:
Main Author: | |
---|---|
Format: | Final Year Project / Dissertation / Thesis |
Published: |
2022
|
Subjects: | |
Online Access: | http://eprints.utar.edu.my/4968/1/ET_1702976_FYP_report_%2D_CHEE_HONG_LEAN.pdf http://eprints.utar.edu.my/4968/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my-utar-eprints.4968 |
---|---|
record_format |
eprints |
spelling |
my-utar-eprints.49682022-12-23T13:34:08Z Disaster resilient mesh network using LoRa and Nervenet Lean, Chee Hong TK Electrical engineering. Electronics Nuclear engineering When a natural disaster event happens, it could cause regional cellular network outages and hence disable network communication within the affected area. If a resilient network is implemented, alert messages with sufficient information can be sent over the Internet to provide a nationwide response. Japan National Institute of Information and Communication Technology has invented a resilient network framework called NerveNet, it supports mesh network where each node will approach other nodes in range if the current peer no longer responds. Using their technology, disaster nodes could be installed at disaster hotspots to send out disaster information or even provide light internet services. NerveNet does support data communication using Wi-Fi and LoRa. NerveNet Wi-Fi-Mesh links are used to provide wide bandwidth but low range data transmission, while NerveNet LoRa-Mesh supports narrow bandwidth data transmission in coverage of kilometers, which is suitable for crucial or emergency disaster data updates. 2022 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/4968/1/ET_1702976_FYP_report_%2D_CHEE_HONG_LEAN.pdf Lean, Chee Hong (2022) Disaster resilient mesh network using LoRa and Nervenet. Final Year Project, UTAR. http://eprints.utar.edu.my/4968/ |
institution |
Universiti Tunku Abdul Rahman |
building |
UTAR Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Tunku Abdul Rahman |
content_source |
UTAR Institutional Repository |
url_provider |
http://eprints.utar.edu.my |
topic |
TK Electrical engineering. Electronics Nuclear engineering |
spellingShingle |
TK Electrical engineering. Electronics Nuclear engineering Lean, Chee Hong Disaster resilient mesh network using LoRa and Nervenet |
description |
When a natural disaster event happens, it could cause regional cellular network outages and hence disable network communication within the affected area. If a resilient network is implemented, alert messages with sufficient information can be sent over the Internet to provide a nationwide response. Japan National Institute of Information and Communication Technology has invented a resilient network framework called NerveNet, it supports mesh network where each node will approach other nodes in range if the current peer no longer responds. Using their technology, disaster nodes could be installed at disaster hotspots to send out disaster information or even provide light internet services. NerveNet does support data communication using Wi-Fi and LoRa. NerveNet Wi-Fi-Mesh links are used to provide wide bandwidth but low range data transmission, while NerveNet LoRa-Mesh supports narrow bandwidth data transmission in coverage of kilometers, which is suitable for crucial or emergency disaster data updates. |
format |
Final Year Project / Dissertation / Thesis |
author |
Lean, Chee Hong |
author_facet |
Lean, Chee Hong |
author_sort |
Lean, Chee Hong |
title |
Disaster resilient mesh network using LoRa and Nervenet |
title_short |
Disaster resilient mesh network using LoRa and Nervenet |
title_full |
Disaster resilient mesh network using LoRa and Nervenet |
title_fullStr |
Disaster resilient mesh network using LoRa and Nervenet |
title_full_unstemmed |
Disaster resilient mesh network using LoRa and Nervenet |
title_sort |
disaster resilient mesh network using lora and nervenet |
publishDate |
2022 |
url |
http://eprints.utar.edu.my/4968/1/ET_1702976_FYP_report_%2D_CHEE_HONG_LEAN.pdf http://eprints.utar.edu.my/4968/ |
_version_ |
1753792999096057856 |
score |
13.214268 |