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Data reinforcement control technique‑based monitoring and controlling of environmental factors for IoT applications

In recent years, environmental monitoring is essential to minimize environmental problems. However, the need for more and more aquatic ecosystems from pollution, increasing climate change, and direct environment loss, so that they can continue to be thoroughly monitored for risks. In this system...

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Main Authors: Mehbodniya, Abolfazl, Haq, Mohd Anul, Kumar, Anil, Ismail, Mohd Erfy, Dahiya, Priyanka, Karupusamy, Sathishkumar
Format: Article
Language:English
Published: Springer 2022
Subjects:
T Technology (General)
Online Access:http://eprints.uthm.edu.my/7494/1/J14383_4830cb99648f93a318f1cd651bf1f02b.pdf
http://eprints.uthm.edu.my/7494/
https://doi.org/10.1007/s12517-022-09917-3
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spelling my.uthm.eprints.74942022-08-15T03:01:00Z http://eprints.uthm.edu.my/7494/ Data reinforcement control technique‑based monitoring and controlling of environmental factors for IoT applications Mehbodniya, Abolfazl Haq, Mohd Anul Kumar, Anil Ismail, Mohd Erfy Dahiya, Priyanka Karupusamy, Sathishkumar T Technology (General) In recent years, environmental monitoring is essential to minimize environmental problems. However, the need for more and more aquatic ecosystems from pollution, increasing climate change, and direct environment loss, so that they can continue to be thoroughly monitored for risks. In this system, the implementation of a data reinforcement control technique (DRCT) using the Internet of Things (IoT) systems is presented to aquatic inquiry environments. In particular, it describes an automated system using data from the design and implementation of recording environ�ments that monitor sensors and installation parameters in lakes and rivers. Design and low-cost real-time monitoring, alert worker development, polluted notification data are confirmed around. Various parameters such as air quality, temperature, humidity, and PIC controller sound intensity sensor, collection, and upload data to the cloud using the Wi-Fi module. It then forwards to a digital dashboard for confirmation on the web via a smartphone or cloud platform exception notification to alert the user. The industry will be the power of closed industrial electricity if they do not take any steps to reduce pollution within a specified period until they are paid under government regulations and pollution control and the amount of pollution in the city. The proposed system is simulated in the PROTEUS 8.1 simulator to analyze the system output. Springer 2022 Article PeerReviewed text en http://eprints.uthm.edu.my/7494/1/J14383_4830cb99648f93a318f1cd651bf1f02b.pdf Mehbodniya, Abolfazl and Haq, Mohd Anul and Kumar, Anil and Ismail, Mohd Erfy and Dahiya, Priyanka and Karupusamy, Sathishkumar (2022) Data reinforcement control technique‑based monitoring and controlling of environmental factors for IoT applications. Arabian Journal of Geosciences, 15. pp. 1-8. https://doi.org/10.1007/s12517-022-09917-3
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Mehbodniya, Abolfazl
Haq, Mohd Anul
Kumar, Anil
Ismail, Mohd Erfy
Dahiya, Priyanka
Karupusamy, Sathishkumar
Data reinforcement control technique‑based monitoring and controlling of environmental factors for IoT applications
description In recent years, environmental monitoring is essential to minimize environmental problems. However, the need for more and more aquatic ecosystems from pollution, increasing climate change, and direct environment loss, so that they can continue to be thoroughly monitored for risks. In this system, the implementation of a data reinforcement control technique (DRCT) using the Internet of Things (IoT) systems is presented to aquatic inquiry environments. In particular, it describes an automated system using data from the design and implementation of recording environ�ments that monitor sensors and installation parameters in lakes and rivers. Design and low-cost real-time monitoring, alert worker development, polluted notification data are confirmed around. Various parameters such as air quality, temperature, humidity, and PIC controller sound intensity sensor, collection, and upload data to the cloud using the Wi-Fi module. It then forwards to a digital dashboard for confirmation on the web via a smartphone or cloud platform exception notification to alert the user. The industry will be the power of closed industrial electricity if they do not take any steps to reduce pollution within a specified period until they are paid under government regulations and pollution control and the amount of pollution in the city. The proposed system is simulated in the PROTEUS 8.1 simulator to analyze the system output.
format Article
author Mehbodniya, Abolfazl
Haq, Mohd Anul
Kumar, Anil
Ismail, Mohd Erfy
Dahiya, Priyanka
Karupusamy, Sathishkumar
author_facet Mehbodniya, Abolfazl
Haq, Mohd Anul
Kumar, Anil
Ismail, Mohd Erfy
Dahiya, Priyanka
Karupusamy, Sathishkumar
author_sort Mehbodniya, Abolfazl
title Data reinforcement control technique‑based monitoring and controlling of environmental factors for IoT applications
title_short Data reinforcement control technique‑based monitoring and controlling of environmental factors for IoT applications
title_full Data reinforcement control technique‑based monitoring and controlling of environmental factors for IoT applications
title_fullStr Data reinforcement control technique‑based monitoring and controlling of environmental factors for IoT applications
title_full_unstemmed Data reinforcement control technique‑based monitoring and controlling of environmental factors for IoT applications
title_sort data reinforcement control technique‑based monitoring and controlling of environmental factors for iot applications
publisher Springer
publishDate 2022
url http://eprints.uthm.edu.my/7494/1/J14383_4830cb99648f93a318f1cd651bf1f02b.pdf
http://eprints.uthm.edu.my/7494/
https://doi.org/10.1007/s12517-022-09917-3
_version_ 1743109091226550272
score 13.211869

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