Visual and geolocation enabled wireless emergency notification system using embedded internet of thing device / Shazrin Irda Ezanee
This project developed an intelligent street light with several smart features such as, WI-FI module, GPS, and HD Camera. The biggest problem that contributes to the existence of this technology is to upgrade the system from manual to automatic system by eliminates the hotline calls between citizen...
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my-uitm-ir.814752024-05-21T06:55:30Z Visual and geolocation enabled wireless emergency notification system using embedded internet of thing device / Shazrin Irda Ezanee 2017 Ezanee, Shazrin Irda Wireless Internet This project developed an intelligent street light with several smart features such as, WI-FI module, GPS, and HD Camera. The biggest problem that contributes to the existence of this technology is to upgrade the system from manual to automatic system by eliminates the hotline calls between citizen and emergency responder. In order to achieve the Internet Telecommunication Union (ITU) standard requirement toward Smart city, using Internet of Thing is one of the requirement. For system improvement, this research is focusing to automate all the manual system (hotline call method) to online based method using Raspberry Pi 3. The main system are using WI-FI module and a few features such as GPS is for location and co-ordinate while the HD Camera is function is to live stream the accident through the monitoring website for reporting to the rescue team. 2017 Thesis https://ir.uitm.edu.my/id/eprint/81475/ https://ir.uitm.edu.my/id/eprint/81475/1/81475.pdf text en public masters Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Idris, Azlina |
institution |
Universiti Teknologi MARA |
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UiTM Institutional Repository |
language |
English |
advisor |
Idris, Azlina |
topic |
Wireless Internet |
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Wireless Internet Ezanee, Shazrin Irda Visual and geolocation enabled wireless emergency notification system using embedded internet of thing device / Shazrin Irda Ezanee |
description |
This project developed an intelligent street light with several smart features such as, WI-FI module, GPS, and HD Camera. The biggest problem that contributes to the existence of this technology is to upgrade the system from manual to automatic system by eliminates the hotline calls between citizen and emergency responder. In order to achieve the Internet Telecommunication Union (ITU) standard requirement toward Smart city, using Internet of Thing is one of the requirement. For system improvement, this research is focusing to automate all the manual system (hotline call method) to online based method using Raspberry Pi 3. The main system are using WI-FI module and a few features such as GPS is for location and co-ordinate while the HD Camera is function is to live stream the accident through the monitoring website for reporting to the rescue team. |
format |
Thesis |
qualification_level |
Master's degree |
author |
Ezanee, Shazrin Irda |
author_facet |
Ezanee, Shazrin Irda |
author_sort |
Ezanee, Shazrin Irda |
title |
Visual and geolocation enabled wireless emergency notification system using embedded internet of thing device / Shazrin Irda Ezanee |
title_short |
Visual and geolocation enabled wireless emergency notification system using embedded internet of thing device / Shazrin Irda Ezanee |
title_full |
Visual and geolocation enabled wireless emergency notification system using embedded internet of thing device / Shazrin Irda Ezanee |
title_fullStr |
Visual and geolocation enabled wireless emergency notification system using embedded internet of thing device / Shazrin Irda Ezanee |
title_full_unstemmed |
Visual and geolocation enabled wireless emergency notification system using embedded internet of thing device / Shazrin Irda Ezanee |
title_sort |
visual and geolocation enabled wireless emergency notification system using embedded internet of thing device / shazrin irda ezanee |
granting_institution |
Universiti Teknologi MARA (UiTM) |
granting_department |
Faculty of Electrical Engineering |
publishDate |
2017 |
url |
https://ir.uitm.edu.my/id/eprint/81475/1/81475.pdf |
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1804889704987885568 |