IoT-Based smart energy-saving streetlights / Nur Amyleena Arnie Faishal Azmi

The conventional street-lighting system in Malaysia promotes high energy consumption. This caused expensive electricity and maintenance bills. One of the approaches to solve this problem is by developing and implementing the IoT-Based Smart Energy Saving Streetlights (SESS). The SESS has two main fe...

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Bibliographic Details
Main Author: Faishal Azmi, Nur Amyleena Arnie
Format: Thesis
Language:English
Published: 2020
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/31524/1/TD_NUR%20AMYLEENA%20ARNIE%20FAISHAL%20AZMI%20CS%20R%2020_5.pdf
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author Faishal Azmi, Nur Amyleena Arnie
author_facet Faishal Azmi, Nur Amyleena Arnie
author_sort Faishal Azmi, Nur Amyleena Arnie
collection UITM
description The conventional street-lighting system in Malaysia promotes high energy consumption. This caused expensive electricity and maintenance bills. One of the approaches to solve this problem is by developing and implementing the IoT-Based Smart Energy Saving Streetlights (SESS). The SESS has two main features, automation in switching on and off and dimming to 40%. These features are enabled through the implementation of LDR and IR sensors which are connected to the LEDs. These components are controlled by a microcontroller, NodeMCU. It has been found that the SESS can reduce up to 79% of the power bills of streetlights. This reduction will be very beneficial to society in general. SESS is beneficial to the government which it allows them to reduce the operating and maintenance costs of streetlights. Meanwhile, the researchers can use the approach to address the similar issues in future works.
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spelling oai:ir.uitm.edu.my:315242020-06-24T08:27:06Z https://ir.uitm.edu.my/id/eprint/31524/ IoT-Based smart energy-saving streetlights / Nur Amyleena Arnie Faishal Azmi Faishal Azmi, Nur Amyleena Arnie Instruments and machines Electronic Computers. Computer Science Electric lighting Detectors. Sensors. Sensor networks The conventional street-lighting system in Malaysia promotes high energy consumption. This caused expensive electricity and maintenance bills. One of the approaches to solve this problem is by developing and implementing the IoT-Based Smart Energy Saving Streetlights (SESS). The SESS has two main features, automation in switching on and off and dimming to 40%. These features are enabled through the implementation of LDR and IR sensors which are connected to the LEDs. These components are controlled by a microcontroller, NodeMCU. It has been found that the SESS can reduce up to 79% of the power bills of streetlights. This reduction will be very beneficial to society in general. SESS is beneficial to the government which it allows them to reduce the operating and maintenance costs of streetlights. Meanwhile, the researchers can use the approach to address the similar issues in future works. 2020-06-24 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/31524/1/TD_NUR%20AMYLEENA%20ARNIE%20FAISHAL%20AZMI%20CS%20R%2020_5.pdf IoT-Based smart energy-saving streetlights / Nur Amyleena Arnie Faishal Azmi. (2020) Degree thesis, thesis, Universiti Teknologi Mara Perlis.
spellingShingle Instruments and machines
Electronic Computers. Computer Science
Electric lighting
Detectors. Sensors. Sensor networks
Faishal Azmi, Nur Amyleena Arnie
IoT-Based smart energy-saving streetlights / Nur Amyleena Arnie Faishal Azmi
title IoT-Based smart energy-saving streetlights / Nur Amyleena Arnie Faishal Azmi
title_full IoT-Based smart energy-saving streetlights / Nur Amyleena Arnie Faishal Azmi
title_fullStr IoT-Based smart energy-saving streetlights / Nur Amyleena Arnie Faishal Azmi
title_full_unstemmed IoT-Based smart energy-saving streetlights / Nur Amyleena Arnie Faishal Azmi
title_short IoT-Based smart energy-saving streetlights / Nur Amyleena Arnie Faishal Azmi
title_sort iot based smart energy saving streetlights nur amyleena arnie faishal azmi
topic Instruments and machines
Electronic Computers. Computer Science
Electric lighting
Detectors. Sensors. Sensor networks
url https://ir.uitm.edu.my/id/eprint/31524/1/TD_NUR%20AMYLEENA%20ARNIE%20FAISHAL%20AZMI%20CS%20R%2020_5.pdf
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